IEA Wind Task 24 Final Report, Vol. 1

1

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy 

Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

IEA Wind Task 24 

Integration of Wind and 

Hydropower Systems 

Volume 1: Issues, Impacts, and 

Economics of Wind and 

Hydropower Integration

Authors: Tom Acker, Northern Arizona 

University on behalf of the National 

Renewable Energy Laboratory

U.S. Department of Energy Wind and 

Hydropower Program

Prepared for the International Energy Agency Implementing 

Agreement for Co-operation in the Research, Development, 

and Deployment of Wind Energy Systems 

Technical Report

NREL/TP-5000-50181 

December 2011

National Renewable Energy Laboratory

1617 Cole Boulevard

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303-275-3000 • www.nrel.gov
NOTICE

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IEA Wind Task 24 Final Report, Vol. 1

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Preface

In November 2003, the International Energy Agency (IEA) Implementing Agreement (IA) for 

Cooperation in the Research, Development, and Deployment of Wind Energy Systems (IEA 

Wind) held Topical Expert Meeting #41 on the Integration of Wind and Hydropower Systems. 

This meeting convened a group of industry, academic, and government officials with expertise in 

wind power, hydropower, and utility and transmission system planning and operation. Their 

purpose was to discuss the potential for coordinated operation of wind and hydropower in 

serving load, the benefits and detriments in doing so, and to identify the related opportunities and 

issues. As a result of this meeting and interactions with the IEA Hydropower IA, a 

recommendation was made to IEA Wind to establish a formal research task to address the 

myriad of questions and unresolved issues pertaining to the topic. Subsequent to this meeting, in 

2004 IEA Wind established a research and development task to investigate the potential for 

integrating wind and hydropower resources on the electrical grid. The research task, also known 

as an “Annex,” was the twenty-fourth such task established by IEA Wind, and was entitled: 

“Task 24: Integration of Wind and Hydropower Systems.” Seven member countries of IEA Wind 

joined the task: Australia, Canada, Finland, Norway, Sweden, Switzerland, and the United 

States. When established, a research and development (R&D) task is assigned an “Operating 

Agent” (i.e., managing director). For Task 24, the National Renewable Energy Laboratory 

(NREL) in the United States, on behalf of the U.S. Department of Energy, was selected as the 

Operating Agent.

The primary purposes of Task 24 were to conduct cooperative research concerning the 

generation, transmission, and economics of integrating wind and hydropower systems, and to 

provide a forum for information exchange. The former of these two purposes was addressed 

through case study projects performed at participating institutions within each member country. 

The latter purpose related to information exchange was accomplished via a series of 

collaborative R&D meetings, seven of which were held: a kickoff 

meeting (February 2005 in the United States); one web meeting 

(June 2006); and five R&D meetings (September 2005 in 

Switzerland, September 2006 in Australia, May 2007 in Italy, 

September 2007 in Norway, and June 2008 in Québec, Canada).

The Task 24 Final Report summarizes and presents the results of the 

work conducted by the task participants, the important issues and 

analysis methods identified, and the related conclusions. The report 

was assembled in two volumes: the first providing objectives, 

background, summary results, and conclusions; and the second 

describing the methods of study employed and details about the

participant case studies upon which the conclusions of the task were 

drawn.
IEA Wind Task 24 Final Report, Vol. 1

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Acknowledgments

Many organizations and people contributed to the Task 24 final report via contributions to the 

various case study projects conducted by the participants, more than can be acknowledged here. 

Thanks are due to all these people. Special recognition is due to the following contributors for 

their participation in the task, its meetings, for oversight of their country’s contributions to the 

case studies, and for organizing their contributions to this report: 

Tom Acker, Ph.D., Northern Arizona University, Operating Agent representative on behalf 

of NREL, primary author and editor

United States

Mr. Robert Zavadil, EnerNex Corporation

Mr. Brian Parsons, National Renewable Energy Laboratory

Mr. Cliff Murley, Sacramento Public Utility District

Mr. Keith Knitter, Grant County Public Utility District

Ms. Patricia Weis-Taylor, PWT Communications, LLC, Secretariat IEA Wind

Marian Piekutowski, Ph.D., Hydro Tasmania

Australia

Mr. Mike Underwood, Hydro Tasmania

Ms. Simone Lelande, Natural Resources Canada

Canada

Mr. André Robitaille, Hydro Québec

Mr. Tom Molinski, Manitoba Hydro

Hannele Holltinen, Ph.D., VTT Technical Research Centre

Finland

Juha Kiviluoma, Ph.D., VTT Technical Research Centre

Mr. John Olav Tande, SINTEF Energy Research

Norway

Mr. Magnus Korpås, SINTEF Energy Research

Mr. Terje Gjengedal, Statkraft

Lennart Söder, Ph.D., KTH Swedish Royal Institute of Technology

Sweden

IEA Hydropower Implementing Agreement

Mr. Niels Nielsen, Kator Research, Secretary of IEA Hydropower IA
IEA Wind Task 24 Final Report, Vol. 1

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List of Acronyms

AEMO Australian Energy Market Operator

AGC Automatic Generation Control

BA Balancing Area

ELCC Effective Load Carrying Capacity 

FCAS Frequency Control Ancillary Services

HVDC High-Voltage Direct Current

IA Implementing Agreement

IEA International Energy Agency

IEA Wind The IEA Implementing Agreement for Co-operation in the Research, 

Development and Deployment of Wind Energy Systems

MAE Mean Absolute Error 

MISO Midwest System Independent Operator 

NREL National Renewable Energy Laboratory, U.S. Department of Energy

NordPool The Nordic Power Exchange: The Single Power Market for Norway, 

Denmark, Sweden, and Finland

NWP Numerical Weather Prediction

O&M Operations and Maintenance

PNCA Pacific Northwest Coordination Agreement 

PUD Public Utility District

R&D Research and Development

RMSE Root Mean Square Error

RTO Regional Transmission Organization

SINTEF The Foundation for Scientific and Industrial Research at the Norwegian

Institute of Technology

TSO Transmission System Operator

U.S. United States

USACE U.S. Army Corps of Engineers 

VTT Technical Research Centre of Finland

WAPA Western Area Power Administration
IEA Wind Task 24 Final Report, Vol. 1

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Executive Summary

This report is the first of a two-volume set. It describes the background, concepts, issues, and 

conclusions related to the feasibility of integrating wind and hydropower, as investigated by the 

members of IEA Wind Task 24. It is the result of a four-year effort involving seven member 

countries and thirteen participating organizations. The companion report, Volume 2, describes in 

detail the study methodologies and participant case studies, and exists as a reference for this 

report.

Worldwide, hydropower facilities possess a significant amount of installed electric generating 

capacity. IEA statistics indicate that at the end of 2001 there was in excess of 450,000 MW of 

installed capacity within IEA member countries, with about half in Europe and half in North 

America. In addition to conventional hydropower, there is more than 80,000 MW of installed 

pumped-hydro capacity in IEA countries. In contrast, utility-scale wind power is relatively new 

in the electric market, but increasing rapidly. In 2003, when the topic of Task 24 was initially 

being discussed, there was just over 31,000 MW of wind power installed, an amount that 

increased to in excess of 140,000 MW by the end of 2009. Competitive costs, coupled with the 

fact that wind is a clean energy resource, make wind energy capacity likely to continue to grow 

substantially over the next two decades. Because of the potential for synergistic operation of 

wind and hydropower facilities, many countries are investigating the opportunity to integrate 

wind and hydropower systems in order to optimize their output through coordinated operation.

The hope is to realize such benefits as lowering the cost of ancillary services required by wind 

energy by taking advantage of the built-in energy storage hydro facilities, the opportunity to 

more effectively utilize existing hydro and transmission facilities, and the potential for 

improving hydrologic operations, as well as to develop an overall energy supply portfolio that is 

more diverse, robust, and cleaner. With wind power penetrations increasing worldwide, the 

topics of Task 24 are more relevant than ever.

For the reasons described above, in 2004, IEA Wind formed research and development Task 24,1

Goal 1) Establish an international forum for exchange of knowledge, ideas, and experiences 

related to the integration of wind and hydropower technologies within electricity 

supply systems.

titled “Integration of Wind and Hydropower Systems.” The primary purposes of this Task are to 

conduct cooperative research concerning the generation, transmission, and economics of 

integrating wind and hydropower systems, and to provide a forum for information exchange. The 

following are specific goals of Task 24:

Goal 2) As it pertains to wind and hydropower integration, share information among 

participating members concerning grid integration, transmission issues, hydrological 

and hydropower impacts, markets and economics, and simplified modeling 

techniques.

 1 It is worth noting here that the topics of the task were discussed and the objectives formed through conversations 

with the IEA Hydropower IA, and formation of a joint task (i.e., sponsored by both IAs) was seriously considered. 

Though a joint task did not materialize, the collaboration strengthened the work plan of the task and the robustness 

of the analysis and conclusions.
IEA Wind Task 24 Final Report, Vol. 1

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Goal 3) Through information sharing and exchange of ideas, identify technically and 

economically feasible system configurations for integrating wind and hydropower, 

including the effects of market structure on wind-hydro system economics with the 

intention of identifying the most effective market structures.

Goal 4) Document case studies pertaining to wind and hydropower integration, and create an 

on-line library of reports.

Task 24 member countries and participating organizations are listed in Table 1. Case studies that 

analyze the feasibility, benefits, detriments, and costs of specific wind-hydro integration projects 

were the mechanism through which the goals of the task were addressed and the feasibility of 

wind-hydro integration was investigated. The general nature of each type of case study is 

described below.

Grid Integration Case Studies

System balancing is one of the primary functions performed by a transmission system operator. 

Ancillary services is the term generally used to describe the services or functions related to the 

operation of a balancing area within an interconnected electric power system necessary for 

maintaining performance and reliability. These services can be broadly categorized as 

operational reserves or contingency reserves. Operational reserves are generally used to respond 

to fast fluctuations in total system net load as well as the more gradual and more predictable 

ramps in net load (net load is defined herein as the system load less wind power, or in other 

words the net load that must be served by the remaining generation fleet). Contingency reserves 

are generation resources, some fast-responding and synchronized, and some off-line that can be 

brought on-line and synchronized relatively quickly (within 10- to 30-minutes, depending on the 

system), used to cover unexpected losses in generation or transmission resources. Grid 

integration studies are frequently aimed at determining the increase in operational and 

contingency reserves, and their related costs, caused by the variability of wind power and 

uncertainty in its prediction.

The wide variety of hydropower installations, reservoirs, operating constraints, and hydrologic 

conditions combined with the diverse characteristics of the numerous electrical grids (balancing 

areas) provide many possible combinations of wind, hydropower, balancing areas, and markets, 

and thus many possible solutions to issues that arise. Hydro generators typically have very quick 

start-up and response times and may have flexibility in water-release timing. Therefore, hydro 

generators could be ideal for balancing increased ancillary service requirements due to wind 

energy fluctuations or even for novel system balancing products such as energy storage and 

redelivery. Studying grid integration of wind energy, particularly on grids with hydropower 

resources, will help system operators understand the potential for integrating wind and 

hydropower resources.
IEA Wind Task 24 Final Report, Vol. 1

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Table 1. Task 24 member countries, contracting parties, and participants

Six of the seven countries participating in Task 24 have contributed at least one case study of this 

nature, covering a wide variety of system configurations, with some representing small systems 

(<1,000 MW peak load), such as Grant County Public Utility in Washington State, United States, 

to large systems (>74,000 MW peak load) such as Nordic system. There is also a wide variety of 

hydropower facilities, with some being essentially run-of-the-river with little storage capacity (a 

day or two), to very large hydro plants with multi-year storage capability.

Hydropower Impact Case Studies

Depending on the relative capacities of the wind and hydropower facilities, wind integration may 

necessitate changes in the way hydropower facilities operate in order to provide balancing, 

reserves, or energy storage. These changes may affect operation, maintenance, revenue, water 

storage, and the ability of the hydro facility to meet its primary purposes. Beyond these potential 

changes, integration with wind could potentially provide benefits to the hydro system related to 

water storage or compliance with environmental regulations (e.g., fish passage) and create new 

economic opportunities. Thus, the purpose of these case studies was to increase understanding of 

the impacts and benefits of wind integration on other aspects of the hydropower system. Three of 

the seven countries participating expect to contribute to these studies. 

Market and Economic Case Studies

While grid integration and hydrologic impact studies may demonstrate the technical feasibility of 

integrating wind and hydropower systems, implementation will often depend on the economic 

feasibility of a given project. Such economic feasibility will depend on the type of electricity 

organization or market in which the wind and hydro projects are considered. Addressing 

economic feasibility in the electricity market will provide insight into which market types are 

practical for wind-hydro integration, as well as identify the key factors driving the economics. 

This understanding may provide opportunities to devise new methods of scheduling and pricing 

that are advantageous to wind-hydro integration and permit better utilization of system resources. 

These market and economic case studies address the effects of today’s market structures on 

Country Contracting Party Participant

Australia Australia Wind Energy Association Hydro Tasmania

Canada Natural Resources Canada Natural Resources Canada

Manitoba Hydro

Hydro Québec

Finland TEKES National Technology Agency in 

Finland

VTT 

Norway Norwegian Water Resources and Energy 

Directorate

SINTEF Energy Research

Statkraft Energy

Sweden Swedish Energy Agency KTH Swedish Institute of Technology

Switzerland Swiss Federal Office of Energy EW Ursern

United States U.S. Department of Energy National Renewable Energy Laboratory

Grant County Public Utility District

Sacramento Municipal Utility District

Northern Arizona University
IEA Wind Task 24 Final Report, Vol. 1

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wind-hydro system economics with the intention of identifying the most effective market 

structures. Economic studies that consider the value of wind energy generation and hydropower 

to the electricity customer are of the greatest interest. Because economic feasibility is germane to 

integrating wind and hydropower, six of the seven participating countries contributed to these 

studies. 

Results of the Task

Though specific wind-hydro integration projects may differ substantially, there are many 

characteristics common to each. Consequently, there was ample opportunity for each participant 

of the task to leverage one another’s case study projects to enhance their own findings, discuss 

difficulties faced in analysis and interpretation of results, and debate methods and conclusions. 

By the end of 2009, six Task 24 participant meetings had been held, as displayed in Table 2. The 

purpose of each of these meetings was similar: to collaborate on ideas and methods used in 

studying wind and hydropower integration, and to communicate, interpret, and sometimes debate 

the methods and results related to specific case studies. 

As a part of this process, a common template for describing and interpreting participant case 

studies was developed, in order to overcome some basic differences in terminology as well as to 

place the study results in the context of the assumptions, the characteristics of the electrical 

balancing area, the wind and hydropower generation, the load, and the other generation 

resources. This common template is described in detail in Volume 2 of this report.

Table 2. R&D meetings of Task 24, including date, location, and host

A summary of conclusions drawn related to each context of wind/hydro integration are provided 

below.

Grid Integration Impacts and Costs

Wind power data from existing wind power plants can provide a good indication for the order of 

magnitude and frequency of wind power output changes with which a system operator or planner 

must deal. The data suggests that there will be a relatively small impact at the regulation 

(minute-to-minute) time scale, but becoming considerable at the hourly time scale and beyond 

(e.g., load following, unit commitment, reserve requirements), especially at high levels of wind 

penetration. In addition to being variable, wind power is also uncertain, and though accurately 

predictable much of the time, can suffer from large forecast errors that may occur at inopportune 

times during system operation. Wind power, while primarily an energy resource, does have a 

capacity value that should be considered in system planning. What makes wind power different 

to a system operator and planner as compared to other power resources is its variability and 

Meeting Location / Host Date

Kickoff Hoover Dam, NV, U.S. / NREL, USBR, APA February 22–23, 2005

R&D #1 Lucerne, Switzerland / EW Ursern September 30, 2005

R&D #2 Launceston, Tasmania, Australia / Hydro Tasmania September 25–26, 2006

R&D #3 Milan, Italy / EWEA May 7, 2007

R&D #4 Oslo, Norway / Statkraft September 19–20, 2007

R&D #5 Québec City, Québec, Canada / Hydro Québec June 5–6, 2008
IEA Wind Task 24 Final Report, Vol. 1

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uncertainty, and learning how to understand and work with these characteristics. The overall 

impact of the wind power variations, forecast errors, and their associated integration cost, 

combined with the cost of wind energy, its marginal value, and the positive benefits it brings to 

the electrical system, depend upon a host of factors including the system load, the generation 

fleet, operational and market flexibility, etc., and can only be accurately estimated via a thorough 

detailed simulation of the power system. Seven case studies of this task addressed wind 

integration impacts and costs, the relevant conclusions of which are summarized below.

• Finnish Case Study #1

•

: This study showed that even with the limited flexibility of 

hydropower (run-of-the-river with small reservoirs), a large part of wind power forecast 

errors can be provided for by shifting hydropower back and forth inside one day. The study 

also showed that when correcting the forecast errors of wind power at a large balancing 

market in which hydropower produces most of the balancing (like in Nordic countries), there 

is no great benefit from combining/integrating wind power and hydropower at a single 

producer. It is more cost effective to bid all flexibility of hydropower to the balancing market 

and use it from there to correct the system imbalances than to use it for dedicated balancing 

of wind power.

Finnish Case Study #2:

•

The study analyzed wind power energy penetrations of 10%, 20%, 

and 30% in the Nordic system (74,000-MW peak load), with the intention of determining 

whether or not there is enough regulation available from the hydropower to deal with 

incremental increase in net power system variations and forecast errors due to wind power. 

The study identified a practical system configuration of 60% of electricity from hydropower, 

most of which is reservoir hydropower, and 30% of electricity from wind power. Results 

showed that a large part of hydropower capacity should be capable of flexible operation and 

able to provide the additional regulation required due to the high penetration of wind power.

Norwegian Case Study #1

•

: This case study analyzed a regional power system with an 

assumed 420-MW power transfer capacity. With regard to integrating wind energy, the most 

conservative approach allows for only 115 MW of wind power in the constrained network 

with 420 MW of capacity, as this will not require any control actions even in the very 

unlikely case of maximum wind and hydro generation (115 MW + 380 MW) at the same 

hour as the historically lowest consumption (75 MW). The results of the study showed that 

for the specific system under consideration, up to 600 MW of wind power is possible—

without noticeable reduction in income from energy sales compared to an ideal noncongested case—by applying coordinated operation of the wind power and hydropower 

plants. 

Norwegian Case Study #2: This case study considered the impact of wind power on system 

adequacy and assessed using data from a real-life, regional, and hydro-based power system. 

Three cases were considered: the installed wind power is 62 MW (Case B) and 1,062 MW 

(Case A and Case C), which correspond to wind power penetration levels of 1.6% (Case B) 

and 28.1% (Case A and Case C). The annual load is 21,024 GWh, which gives wind energy 

penetration levels of 0.9% (Case B) and 15.2% (Case A and Case C). The study concluded 

that wind power will have a positive effect on system adequacy in a regional hydro-based 

power system. Wind power contributes to reducing the loss of load probability and to 

improving the energy balance. Adding 3 TWh of wind or 3 TWh of gas generation are found 

to contribute equally to the energy balance, both on a weekly and annual basis. Both wind 
IEA Wind Task 24 Final Report, Vol. 1

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and gas improves the power balance. The capacity value of gas is found to be about 95% of 

rated, and the capacity value of wind about 30% at low-wind energy penetration, and about 

14% at higher wind penetration.

• Swedish Case Study #2

•

: The aim of the simulation in the second Swedish case study was to 

study the possibility of balancing wind power in northern Sweden using hydropower in 

northern Sweden. The simulation included a total installed capacity of 795 MW of wind 

power, and that output was scaled to 1,000; 4,000; 8,000; and 12,000 MW. All hydropower

stations larger than 10 MW in the studied area were considered (i.e., 154 hydropower plants 

with a combined capacity of 13.2 GW), which corresponds to about 80% of the installed 

capacity of all hydropower in Sweden. The conclusion of the study was that the existing 

hydropower in northern Sweden has sufficient installed capacity and is fast enough to 

balance even large amounts of wind power. The model predicted spill to occur, but, to an 

overwhelming extent, such a spill can be avoided by using efficient tools, especially for

season planning. Only in a few cases—and then in particular for a wind power expansion of 

12,000 MW—will there be spill that depends on insufficient balancing capability in the 

hydropower.

U.S. Case Study on the Missouri River

•

: The case study on the Missouri River analyzed wind 

integration into the balancing area operated by the Western Area Power Administration 

(WAPA) and supplied by hydropower facilities located along the Missouri River. This study 

considered integrating five levels of wind power penetration of 3%, 3.7%, 9.3%, 18.6%, and 

37%. The hydropower capacity is 2,400 MW from six hydro facilities containing multiple 

years of water storage, and the peak system load was 2,700 MW. The statistical study 

concluded that in the WAPA system, significant operational impacts from wind energy—

those that must be dealt with in planning and operation (regulation, load following, system 

ramping of net load)—will likely arise when the wind penetration approaches 500 MW 

(about 18% of the peak system load). 

U.S. Case Study Sacramento Municipal Utility District: This case study focused on 

hydropower resources along the upper American River and operated by the Sacramento 

Municipal Utility District. Hourly simulation cases were completed for at least one full year 

of data for four proposed wind generation penetration levels: 102 MW, 250 MW, 450 MW, 

and 850 MW. These correspond to the following wind penetration levels (computed by 

dividing wind capacity by system peak load): 2.7%, 6.7%, 12.1%, and 22.8%. The study 

found lower penetrations of wind generation have only a small impact on fast regulation 

requirements, but begin to dominate as the penetration increases. Wind integration costs were 

computed to range from about $2 to $8/MWh of wind energy produced. The results show a 

very substantial reduction in operating cost and integration costs with the hypothetical Iowa 

Hill pumped-storage facility operating (as much as $5/MWh). Furthermore, the results also 

show that integration costs decrease with increasing diversity of wind generation assets.

Hydropower Impacts

Hydropower generators are inherently flexible, but in practice their flexibility depends on a host 

of factors. The type and magnitude of ancillary services and reserves that can be provided by a 

hydropower plant depends on whether it possesses significant storage or if it is a run-of-the-river 

plant with limited storage. The flexibility of operation also depends on whether or not the 

hydropower is part of a cascade of dams on a river system, and the level of coordination between 
IEA Wind Task 24 Final Report, Vol. 1

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those on the same river. Hydro facilities often have numerous functions—power generations 

being one—that guide their operation and define their flexibility. Layered on top of the physical 

and functional planning, there may be numerous organizations and stakeholders involved, along 

with differing market or economic situations. It is the interaction of the many functions, system 

configurations, and stakeholders that establish the authority, priority, and economics that govern 

the potential for wind and hydro integration. 

The overarching question for studying wind and hydropower integration is whether systemoperating impacts due to wind power can be accommodated by hydropower within the

constraints currently in place on hydropower (or not easily changed), and in an economically 

advantageous way. And if so, what changes will this cause to hydropower operations or costs? In 

concept, hydropower should be able to provide short- to medium-term buffering of the enhanced 

variability and uncertainty wind power induces in the overall load net wind. Adding wind power 

to the system may or may not help hydropower meet power and other system demands, and the 

influence on other hydro functions, such as water deliveries, must be considered. That said, even 

within the constraints currently imposed on hydropower, it is a valuable system balancing 

resource, and possesses the inherent qualities needed to facilitate wind integration. Five of the 

case studies of Task 24 addressed hydropower impacts, the relevant conclusions of which are 

summarized below.

• Australian Case Studies #1 and #3

•

: Hydro Tasmania’s system was modeled with 1,850 MW 

of peak load; a 900-MW minimum load; 2,267 MW of hydropower, and 630-MW/480-MW 

export/import capability via a high-voltage direct current (HVDC) interconnect with the 

Australian mainland. The studies found that a high level of wind power can be integrated into

the Tasmanian system, up to 1,300 MW, if the interconnect with the Australian mainland is 

used and if measures are taken to address low system inertia. The study also identified that 

commitment of additional hydro generators operating in either synchronous condenser mode 

or tail water depression mode can largely improve the integration of the wind generation in 

Tasmania and mitigate problems associated with low system inertia.

Australian Case Study #2

•

: With respect to reservoir storage, in the case of islanded operation 

of a Tasmanian power system, system storage is unable to effectively absorb all output from 

large-scale wind generation due to coincident of high winds and high inflows. There is an 

increasing negative impact on storage as wind generation capacity is increased. 

Interconnecting to the Australian mainland, via the addition of the high-capacity HVDC 

interconnection, significantly increases the ability to integrate wind generation in Tasmania 

without a negative effect on the energy in storage. 

Swedish Case Study #1: The first Swedish case study analyzed the possibility of balancing 

wind power with hydropower plants located along one certain river. The amount of wind 

power studied extrapolated to a penetration in whole Sweden equal to 6.5–7.5 TWh/year, or

5% of the total energy production per year. The results from the simulations indicate that 

Swedish wind power installations that generate about 2–2.5 TWh/year do not affect the 

efficiency of the Swedish hydro system. At wind power levels of about 4–5 TWh/year, it is 

estimated that the amount of installed wind power should be increased by about 1% to 

compensate for the decreased efficiency in the hydro system. At wind power levels of about 

6.5–7.5 TWh/year, the additional wind power needed to compensate for loss of hydro 

efficiency is about 1.2%, but this figure has to be verified with more extended simulations.
IEA Wind Task 24 Final Report, Vol. 1

xiii

• U.S. Case Study Grant County Public Utility District (PUD): This case study considered two 

hydropower plants located along the Columbia River and operated by the Grant County 

Public Utility District No. 2 (Grant PUD). The levels of wind penetration considered in were

12 MW (1.8%), 63.7 MW (7.8%), and 150 MW (18.6%), with each percentage computed as 

a percentage of peak load (including sales of energy). Study results for the 2006 data year 

suggest that the overall impact on system statistics for regulation and load following is quite 

modest, even at a wind energy penetration of 150 MW (~19% wind penetration by capacity).

The small statistical impact suggests that, absent other constraints, the physical generation 

resources are sufficient to handle wind variability at this level. However, due to changes in 

the distribution of load following hourly changes, there are some potentially significant 

operational challenges in scheduling the resources without infringing upon system 

constraints. To address this, an hourly simulation was conducted using day-ahead wind 

power forecasts, revealing that additional instances of dipping into contingency reserves 

occur due to missed wind power forecasts, and that additional short duration excursions 

below the minimum flow requirements (for fish survival) also occur. The increases, however, 

are only modest and many can likely be handled during the day of operation, though at some 

cost.

Economics

The wind integration and hydro system impact studies have demonstrated the technical 

feasibility of integrating wind power and hydropower, even in systems with either transmission 

or hydropower constraints. Beyond the technical feasibility, two case studies investigated 

whether or not integrating wind was practical from an economic point of view, or looked at the 

effect of wind integration on the market. These two studies represent a valuable contribution to 

the Task, and are a good start in addressing the overall question of economic feasibility.

• Canadian Case Study

•

: Natural Resources Canada conducted a study for a small public utility 

in the U.S. along the Columbia River that demonstrated that using wind power to address 

load growth is economically feasible. It was also shown that the hydropower resources 

available to the utility being studied were satisfactory to supply low-cost balancing resources. 

In practice, due to underproduction of the wind power plant, it was found that the wind 

power would not have been economically favorable without Renewable Energy Production 

Incentives. 

Finnish Case Study #2: The study analyzed wind power energy penetrations of 10%, 20%, 

and 30% in the Nordic system (74,000-MW peak load). Because old power plants were not 

retired in the study, there were no problems with system adequacy. Balancing this amount of 

wind power was shown to be feasible, but it was determined that a large penetration of wind 

power in a hydro-dominated power system will lower the spot price of electricity 

dramatically, which creates a challenge to get new investments in the system. It is unclear 

whether this kind of system could arise based on the markets even if it would be the most 

cost-effective way to serve load from a system perspective.
IEA Wind Task 24 Final Report, Vol. 1

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As the breadth of the case studies indicate, integrating wind and hydropower can be quite 

complex. A summary of some key observations and conclusions from the work and discussion 

among the participants are provided below.

• Figure 1 provides a conceptual view of a practical configuration for combining wind and 

hydropower in a balancing area. The key take-away from this illustration is that wind and 

hydropower are system resources that help serve the load via the transmission grid, and that 

they are each controlled by the transmission system operator (TSO). Addressing the 

incremental impacts of wind integration is done in the context of the entire system, with all 

of its load and generation resources, and not in isolation from them (i.e., not one wind power 

plant balanced by one hydro plant to produce a flat output). 

• When addressing wind integration, one should consider the holistic impact of wind power on 

the system (e.g., a cost-benefit analysis directed toward the electricity customer and the effect 

on transmission system reliability), and not just the enhanced balancing requirements due to 

wind power’s variability and uncertainty. For example, wind power will enhance balancing 

requirements and incur an “integration” cost; however, at the same time, the overall cost of 

electricity to the consumer may decrease due to wind energy displacing higher cost 

generation resources.

• The setup and operation of the transmission system and balancing area authority will have a 

profound impact on the ability to integrate wind power and the integration costs incurred.

TSOs, where the timing of transactions (committing units, buying and selling of electricity, 

ancillary services, and reserves) is frequent, are more capable of integrating wind power and 

at lower costs. 

• Transmission interconnections are important as they can limit wind and hydropower 

integration due to transmission constraints or congestion, or facilitate integration via power 

exchanges with neighboring systems. Larger balancing areas can more easily integrate wind 

and hydropower.

• Electrical systems can function within a liberalized electricity market, via a vertically 

integrated utility that participates with neighboring systems via bilateral transactions, or some 

combination of the two. Wind integration costs and impacts tend to be reduced in market 

systems, especially those with many market actors and flexible resources.

• The wind/hydro case study results were consistent with other wind integration studies in that 

the presence of an efficient and liquid electricity market has a large positive influence on the 

economics, frequently dominating all other factors. Furthermore, an important factor in 

interpreting the economic consequences of integrating wind and hydro is the perspective 

taken by the study: for the overall benefit of the electric customer vs. a single actor in the 

market (e.g., a utility or wind developer).

• In conducting wind integration studies, the modeling assumptions and techniques can have a 

significant influence on the results. Therefore, these should be well-specified and understood 

when interpreting results and comparing different studies. Wind integration studies often 

involve the use of production cost models that simulate hourly operation of the power 

system. General production cost models (those not specifically developed for or by a

hydropower-dominant utility) need improvements in how they model hydropower operation, 

water balances, and constraints, in order to better investigate the nuances of wind and hydro 
IEA Wind Task 24 Final Report, Vol. 1

xv

integration (e.g., the impact of enhanced system balancing requirements on hydro system 

constraints or the ability to model the constraints). Virtually all production cost models

require further improvement in how they handle wind power and wind power forecasts.

• At low wind penetration levels (~1%), wind integration impacts and costs are minor. These 

transition to more cost and complexity as penetration levels increase to ~20%. Beyond ~20%, 

changes in system operational practices are likely necessary to optimally integrate wind and 

hydropower (e.g., use of advanced wind forecasting models incorporated into system 

planning). Islanded or small power systems with weak interconnections may more readily 

experience the effects of the enhanced variability in net load and increased reserve 

requirements caused by wind integration, including impacts on system inertia, and require 

attention in system planning.

• Non-power constraints on the hydropower system can influence the ability to integrate wind 

and hydropower. Such constraints may include higher priority functions of the hydro facility 

that dictate how water is run through the generators, such as irrigation water deliveries, 

environmental regulation (e.g. fish passage), recreation, or flood control. While these nonpower constraints are important, they frequently occur on time scales of system operation 

different than those related to wind/hydro integration. Therefore, they do not tend to be 

prohibitive and often may not significantly influence the wind and hydro integration, 

although at times they do reduce hydro system flexibility. Of the Task 24 participants, these 

constraints only played a significant role in hydro systems in the United States.

In summary, while hydropower systems possess special characteristics and operating constraints, 

the inherent flexibility of their generators and the potential for energy storage in their reservoirs 

make them well suited to integrate wind into the power system. As wind penetration increases, 

the agile hydro generation can address wind integration impacts and this service represents an 

economic opportunity for many hydro generators.

Balancing Area

System Operator / TSO

Thermal

Generation

Loads

Transmission/Distribution Power to grid

Transmission 

Interconnections

Power to grid

Power from grid

Power to grid Power to grid Wind 

Power Hydro

Power

Figure 1. A practical configuration for wind and hydropower integration (Source: T. Acker 

presentation, Task 24 R&D Meeting #5, Québec City, Québec, Canada, June 2008)
IEA Wind Task 24 Final Report, Vol. 1

xvi

Table of Contents

Preface ........................................................................................................................................iii

Acknowledgments .....................................................................................................................iv

List of Acronyms.........................................................................................................................v

Executive Summary...................................................................................................................vi

Grid Integration Case Studies .................................................................................................vii

Hydropower Impact Case Studies..........................................................................................viii

Market and Economic Case Studies ......................................................................................viii

Grid Integration Impacts and Costs......................................................................................... ix

Hydropower Impacts ............................................................................................................... xi

Economics..............................................................................................................................xiii

1 Background Information and Objectives of Task ...............................................................1

1.1 Electric Utilities and System Operation ......................................................................4

1.1.1 Electric Utilities and Markets .................................................................................4

1.1.2 Ancillary Services for Power System Reliability, Security, and Power Quality ......5

1.1.3 How Ancillary Services are Provided.....................................................................8

1.1.4 Time Frames of System Planning .......................................................................10

1.1.5 System Resource Adequacy ...............................................................................12

1.2 What is “Wind and Hydropower Integration”? ..........................................................12

1.3 Task 24 Objectives and Means to Achieve ..............................................................14

1.3.1 Grid Integration Case Studies .............................................................................14

1.3.2 Hydro System Impact Case Studies....................................................................16

1.3.3 Market and Economic Case Studies ...................................................................17

1.3.4 Simplified Modeling of Wind-Hydro Integration Potential ....................................17

1.3.5 Results Expected ................................................................................................17

1.4 Report Organization.................................................................................................18

2 Wind Energy Overview ........................................................................................................19

2.1 The Value of Wind Energy .......................................................................................19

2.2 Characteristics of Wind Power Variability ................................................................21

2.2.1 Variability in the 1-Minute Time Frame................................................................21

2.2.2 Variability in the 10-Minute Time Frame..............................................................23

2.2.3 Variability in the 1-Hour Time Frame...................................................................25

2.2.4 Variability in the Daily, Seasonal, and Yearly Time Frame..................................26

2.3 Characteristics of Wind Power Ramping..................................................................30

2.4 Impact of Geographic Diversity and Aggregation of Wind Power Plant Output on 

Wind Power Variations.............................................................................................32

2.5 Wind Power Forecasting and Uncertainty................................................................34

2.6 Capacity Value of Wind Resources..........................................................................38

2.7 Environmental Attributes ..........................................................................................39

2.8 Summary of Wind Variability and Uncertainty: Considerations in System Planning 

and Operation ..........................................................................................................40

3 Hydropower System Planning and Operation...................................................................41

3.1 Introduction ..............................................................................................................41

3.2 Types of Hydropower and Energy Storage ..............................................................42

3.2.1 Hydro Storage .....................................................................................................43

3.2.2 Run-of-the-River Hydro .......................................................................................43

3.2.3 Pumped Storage .................................................................................................44

3.2.4 Other Non-Hydropower Storage..........................................................................44

3.2.4.1 Flow Batteries................................................................................................44
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3.2.4.2 Batteries ........................................................................................................45

3.2.4.3 Superconducting Magnetic Energy Storage ..................................................45

3.2.4.4 Flywheels.......................................................................................................45

3.2.4.5 Compressed Air Energy Storage...................................................................45

3.2.4.6 Hydrogen .......................................................................................................46

3.2.5 Summary of Storage Options ..............................................................................46

3.3 River Systems ..........................................................................................................47

3.3.1 Example River System with Multiple Owner/Operators: the Columbia River in the 

United States and Canada ..................................................................................48

3.3.2 Example River System with a Single Owner/Operator: the Missouri River in the 

United States.......................................................................................................51

3.3.3 Summary of River Systems.................................................................................52

3.4 Hydropower Generators and Ancillary Services ......................................................52

3.5 Multi-Purpose Hydro Facilities .................................................................................58

3.6 Institutional, Organizational, and Legal Issues Related to Hydropower...................58

3.6.1 Example of a Organizational and Legal Complexity: The Colorado River System 

in the United States .............................................................................................59

3.6.2 Summary .............................................................................................................62

3.7 Variability and Uncertainties of Hydro Resource Across Time Frames of Importance 

in Balancing Area Operation ....................................................................................63

3.8 Planning of the Hydro System..................................................................................67

3.9 Social and Environmental Impacts...........................................................................68

3.10 Summary: Hydropower as a Balancing Resource and Energy Storage ..................68

4 Power System Planning and Operation in Systems with Wind and Hydropower..........71

4.1 Introduction ..............................................................................................................71

4.2 Wind Power Impacts in Systems with Hydropower..................................................71

4.2.1 Results from Recent Wind Integration Studies....................................................71

4.2.2 Review of Results from IEA Wind Task 25..........................................................73

4.2.3 Wind Integration in Systems with Hydropower: Summary of Results from 

Participant Case Studies .....................................................................................76

4.2.3.1 Australian Case Studies ................................................................................77

4.2.3.2 Canadian Case Studies.................................................................................80

4.2.3.3 Finnish Case Studies.....................................................................................81

4.2.3.4 Norwegian Case Studies ...............................................................................84

4.2.3.5 Swedish Case Studies...................................................................................86

4.2.3.6 United States Case Studies...........................................................................88

4.2.4 Practical System Configuration ...........................................................................92

5 Conclusions..........................................................................................................................94

5.1 Grid Integration Impacts and Costs..........................................................................95

5.2 Hydropower Impacts ................................................................................................97

5.3 Economics................................................................................................................98

5.4 System Configuration and General Conclusions .....................................................99

6 References..........................................................................................................................101

Appendix A: Bibliography of Reports...................................................................................105
IEA Wind Task 24 Final Report, Vol. 1

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List of Figures

Figure 1. A practical configuration for wind and hydropower integration (Source: T. Acker 

presentation, Task 24 R&D Meeting #5, Québec City, Québec, Canada, June 2008).................. xv

Figure 2. Average cumulative wind and wholesale power prices over the past 6 years in the 

United States (Source: Wiser and Bolinger 2009)............................................................................. 2

Figure 3. An illustration of the many regional transmission organizations that have arisen in 

Canada and the United States (Source: www.ferc.gov/industries/electric/indus-act/rto/rtomap.asp)................................................................................................................................................ 5

Figure 4. Time scales of importance when considering ancillary service impacts of integrating 

wind energy in the power system (Source: National Renewable Energy Laboratory).................. 7

Figure 5. Typical time frame for planning operations at the Grant County PUD in the United 

States (Source: adapted from Acker et al. 2007)............................................................................. 11

Figure 6. Timeline for day ahead, hour(s) ahead, and real-time planning operations for the Nordel 

system (Source: M. Olsson presentation, Task 24 R&D Meeting #2, Launceston, Tasmania 

2006)..................................................................................................................................................... 11

Figure 7. Overall perspective of the value derived from integrating wind into a utility system 

(Source: Acker 2007a)........................................................................................................................ 21

Figure 8. Distribution of 1-minute step changes and ramp rates based upon 1-minute data for a 

103.5-MW wind power plant in Southwest Minnesota, U.S. (Source: Wan 2004) ........................ 22

Figure 9. Distribution of hourly step changes as a percentage of capacity for a 103.5-MW wind 

power plant in Minnesota, U.S. (Source: Wan 2004)....................................................................... 25

Figure 10. A 1-week trace of 1-minute power output from two wind power plants of nameplate 

capacity 103.5 MW and 113.25 MW, located 200 km apart (Source: Wan 2004) .......................... 27

Figure 11. Average diurnal profile of the wind power output of a 103.5-MW wind power plant 

over 3 months in the autumn (left) and summer (right), for 4 consecutive years 

(Source: Wan 2004) ............................................................................................................................ 28

Figure 12. Plot showing the diurnal variation of output from a small wind power plant during 

January 2004 (Source: Acker et al. 2006)......................................................................................... 28

Figure 13. Monthly energy production for a single power plant (left) and for several power plants 

(right), for several years of operation (Source: Wan 2008)............................................................ 29

Figure 14. Energy production as a percent of the annual average for several wind power plants

near McCamey, Texas, U.S.; the solid red line represents the total energy production from 

aggregating all power plants together (cumulative nameplate capacity of ~690 MW) (Data 

source: NREL)..................................................................................................................................... 29

Figure 15. Distribution of hourly ramping rate values (Source: Wan 2004)........................................ 30

Figure 16. A methodology for defining ramp rates at a wind power plant using a 15-minute rolling 

average of the 1-minute power output data, neglecting changes less than 10-minutes in 

duration when defining the end points of the each ramp .............................................................. 31

Figure 17. Positive (left plot) and negative (right plot) ramps rates expressed as a percentage of 

plant nameplate capacity at the 63.7-MW Nine Canyon Wind power plant in Washington, U.S., 

during 2006.......................................................................................................................................... 32

Figure 18. Table demonstrating the distribution and duration of ramp events at the 63.7-MW Nine 

Canyon Wind power plant in Washington, U.S., during 2006 (magnitudes are in megawatts 

and durations are in minutes) ........................................................................................................... 32

Figure 19. Correlation coefficient between spatially separated wind power plants plotted as a 

function of the distance between them, for their 1-second, 1-minute, 10-minute, and 1-hour 

average power outputs (Source: Wan 2005).................................................................................... 34

Figure 20. Plot of a wind power forecast from WEPROG’s MSEPS system (see www.weprog.com/) 

including uncertainty bands (black and gray shading); a few methods of predicting the 

expected output (orange dashed, white, and yellow lines); and the predicted maximum and 

minimum possible values (top red and bottom green lines)—the actual output is shown by the 

bold, black, dashed line (Source: Ernst et al. 2007)........................................................................ 35

Figure 21. Plots of the mean absolute error (MAE) and root mean square error (RMSE) versus 

number of hours of lead time for the forecast, for a wind power plant in the U.S.; the errors for 

three types of forecasts are displayed: professional, persistence, and climatological 
IEA Wind Task 24 Final Report, Vol. 1

xix

(Source: Northern Arizona University)............................................................................................. 37

Figure 22. Plot of the hour-ahead mean absolute error, sorted by the hourly change in output of 

the wind power plant; the blue, dashed line corresponds to the mean absolute error, the black 

line denotes the frequency of occurrences in each bin of hourly changes, and the red cross 

identifies the overall mean absolute error (for all hours, regardless of hourly change) 

(Source: Northern Arizona University)............................................................................................. 38

Figure 23. A plot demonstrating the hour-ahead MAE and cumulative frequency count as a 

function of the hourly change in wind power plant output (Source: Northern Arizona 

University) ........................................................................................................................................... 38

Figure 24. The capacity value of wind power as determined in several wind integration studies in 

the United States (Source: Smith et al. 2007).................................................................................. 39

Figure 25. (a) Typical configuration of a dam and hydropower plant; (b) a pumped-hydropower 

plant (Source: Tennessee Valley Authority, www.tva.gov/power/hydro.htm) ............................. 43

Figure 26. A “Flexibility Supply Curve” that qualitatively compares the various options for 

provision of ancillary services (Source: Nickell 2008) ................................................................... 47

Figure 27. Map of dams in the Columbia River Basin (Source: U.S. Army Corps of Engineers, 

www.nwd.usace.army.mil/ps/colbsnmap.htm)................................................................................ 49

Figure 28. Plot showing the discharge of water from Grand Coulee dam and from Priest Rapids 

dam during a week in March 2001 (Source: Acker et al. 2006)...................................................... 50

Figure 29. Figure displaying the Missouri River Basin in the United States and the six large 

mainstream dams and hydropower facilities (Source: USACE).................................................... 51

Figure 30. Hypothetical hydropower plant efficiency curves for two different power plants 

(Source: B. Smith, Oak Ridge National Laboratory) ....................................................................... 54

Figure 31. A plot displaying the Hoover power plant efficiency for a typical day of operation, 

captured by taking a “screen shot” from the Hoover Supervisory Control and Data 

Acquisition system (Source: U.S. Bureau of Reclamation, Hoover Power Plant)....................... 55

Figure 32. A “screen shot” from the Hoover power plant Supervisory Control and Data 

Acquisition system, showing numerous parameters concerning unit operation 

(Source: U.S. Bureau of Reclamation, Hoover Power Plant) ......................................................... 56

Figure 33. A typical production pattern from generators at the Hoover power plant during a day 

in November 2007 (Source: U.S. Bureau of Reclamation, Hoover Power Plant) ......................... 57

Figure 34. Illustration of the upper and lower drainage basins of the Colorado River (Source: U.S. 

Bureau of Reclamation) ..................................................................................................................... 59

Figure 35. Day-ahead flow estimates versus actual flow from the Chief Joseph Dam in 

Washington, U.S., provided by USACE, for the month of January 2004 (Source: Grant 

County Public Utility District)............................................................................................................ 65

Figure 36. A time-series plot of the annual flow measured on the Colorado River in the 

Southwestern United States, demonstrating annual and long-term variability (Source: USGS 

2004)..................................................................................................................................................... 66

Figure 37. The intra-daily volatility of inflow to the Ross hydropower facility and the hypothetical 

power output from a wind power plant at Goodnoe (left), both located in Washington, U.S.; 

and, the average operating capacity from May to September for the same two power plants 

(right) (Source: Westrick et al. 2003)................................................................................................ 66

Figure 38. Time horizons of relevance in the hydro system with respect to the hydro impoundment 

(blue), biological communities (green), hydropower (yellow), related to the time scales of wind 

power variability (Source: Oak Ridge National Laboratory) .......................................................... 67

Figure 39. Results for the increase in reserve requirement due to wind power (Source: Holttinen 

et al. 2009) ........................................................................................................................................... 75

Figure 40. Results from estimates for the increase in balancing and operating costs due to wind 

power; the currency conversion used here is 1 € = 0.7 £ and 1 € = 1.3 US$ (Source: Holttinen 

et al. 2009) ........................................................................................................................................... 76

Figure 41. Capacity credit of wind energy as computed in several of the Task 25 case studies 

(Source: Holttinen et al. 2009)........................................................................................................... 76

Figure 42. Wind integration costs for four wind integration penetration levels: Case 1 with 102 MW, 

Case 2 with 250 MW; Case 2 with 450 MW, and Case 3 with 850 MW; these correspond to wind 

penetration levels as a percent of peak system load of 2.7%, 6.7%, 12.1%, and 22.8%; tor each 
IEA Wind Task 24 Final Report, Vol. 1

xx

case, five different strategies for providing system balancing were considered (Source: 

Zavadil 2008) ....................................................................................................................................... 90

Figure 43. Number of exceedences (dropping below) the minimum allowable capacity due to a 

flow constraint, for the system as run and with 63.7 MW of wind planned into the system in 

the day-ahead preschedule (Source: Acker 2007).......................................................................... 92

Figure 44. A practical configuration for wind and hydropower integration (note the red dashed 

lines in the figure refer to information flow including generation control signals) (Source: T. 

Acker presentation, Task 24 R&D Meeting #5, Québec City, Québec, Canada, June 2008)....... 93

List of Tables

Table 1. Task 24 member countries, contracting parties, and participants....................................... viii

Table 2. R&D meetings of Task 24, including date, location, and host................................................ ix

Table 3. Task 24 member countries, contracting parties, and participants.......................................... 4

Table 4. Types of operational reserves employed by TSOs in planning for balancing load and 

generation for three time scales of relevance (Source: adapted from IEA 2005).......................... 9

Table 5. Statistical summary of the magnitude of 1-minute generation changes at a 103.5-MW 

wind power plant Minnesota, U.S. (Source: Wan 2004).................................................................. 23

Table 6. Statistical summary of the aggregated 1-minute generation changes at seven wind power 

plants located in Minnesota, Iowa, and Texas, U.S., with a total installed capacity over 790 

MW (Source: Wan 2004)..................................................................................................................... 23

Table 7. Statistical summary of step changes in the 10-minute average wind power at a 103.5-MW 

wind power plant Minnesota, U.S. (Source: Wan 2004).................................................................. 24

Table 8. Statistical summary of the step changes in the 10-minute average wind power at seven 

wind power plants located in Minnesota, Iowa, and Texas, U.S., with a total installed capacity 

over 790 MW (Source: Wan 2004)..................................................................................................... 24

Table 9. Statistical summary of step changes in the 1-hour average wind power at a 103.5-MW 

wind power plant in Minnesota, U.S. (Source: Wan 2004) ............................................................. 26

Table 10. Statistical summary of the step changes in the 1-hour average wind power at seven 

wind power plants located in Minnesota, Iowa, and Texas, U.S., with a total installed 

capacity over 790 MW (Source: Wan 2004)...................................................................................... 26

Table 11. Statistical summary of ramp rates at a 103.5-MW wind power plant in Minnesota, U.S., 

based upon hourly power data (Source: Wan 2004)....................................................................... 30

Table 12. Step changes in wind power output from groupings of wind turbines located in 

Minnesota, U.S. (Source: Wan 2005) ................................................................................................ 33

Table 13. Approximate capital costs, efficiency, capacity, and level of maturity of various 

alternative energy storage technologies ......................................................................................... 46

Table 14. Summary of hydro plant storage characteristics and potential for use in provision of 

ancillary services and system balancing......................................................................................... 69

Table 15. Wind integration costs in U.S. dollars per MWh of wind energy produced from several 

recent studies in the United States (Source: Wiser 2009).............................................................. 73

Table 16. Power system size and wind power penetration studied in national cases (Source: 

Holttinen et al. 2009)........................................................................................................................... 74
IEA Wind Task 24 Final Report, Vol. 1

1

1 Background Information and Objectives of Task

Over the past several years, concern has increased regarding meeting the growing electrical 

demand while also protecting the environment. As a result, an emphasis on building new, clean, 

renewable energy resources has arisen, often manifested via politically mandated standards, a 

perceived need to cut carbon emissions, or the introduction of new, more cost-effective energy 

generation. Hydropower and wind power are examples of two renewable resources being called 

upon to meet the need for new generation, and they are also among the most affordable. 

Worldwide, hydropower facilities represent a significant amount of installed electric generating 

capacity, responsible for 12.3% of electrical energy generation in 2007 (IEA 2008). IEA 

statistics indicate that at the end of 2000, there was in excess of 410,000 MW of installed 

hydropower capacity within IEA member countries, with about half in Europe and half in North 

America. Since then, hydropower generation has increased by more than 13,000 MW in IEA 

member countries (IEA 2008). Hydropower is typically one of the least expensive generation 

sources, often with generators that are outfitted with automatic generation controls (AGCs) that 

allow very rapid response to changes in electricity demand. Hydropower generators can supply 

valuable “ancillary services” required to maintain the instantaneous balance between generation 

and load. The ability of hydropower to provide these services, along with its low-cost energy 

and, in some cases, energy storage, make it one of the most flexible and valuable generation 

assets on the grid.

Over the past decade, electrical energy derived from utility-scale wind turbines (with capacity 

ratings greater than 1 MW per turbine) has become cost competitive relative to conventional 

electrical energy resources, especially natural-gas-based generation (see Figure 1). Furthermore, 

as wind turbine technology has developed, turbine reliability has become very high (with greater 

than 98% availability), and there is now significant experience in designing, financing, building, 

and operating large wind power plants. As a result, the installed capacity of wind power has 

increased dramatically during the last decade, from 15,400 MW in 2000 to in excess of 

120,000 MW at the end of 2008 (IEA 2008, USDOE 2009). This significant growth is expected 

to continue over the next several years. In addition to its cost competitiveness, wind energy 

brings other benefits—it has long-term price stability, no emission of climate-change gases, 

requires no water, is an indigenous resource, and can foster rural economic development. 
IEA Wind Task 24 Final Report, Vol. 1

2

Figure 2. Average cumulative wind and wholesale power prices over the past 6 years in the United 

States (Source: Wiser and Bolinger 2009)

While wind energy has many positive aspects, it also has different generation characteristics than 

conventional utility resources. In particular, because meteorological processes drive wind, it is 

inherently variable. This variability occurs on all time frames of utility operation from real-time, 

minute-to-minute fluctuations through yearly variation affecting long-term planning. In addition 

to being variable, it is also a challenge to accurately predict wind energy production on the time 

scales of interest to utility planners and operators: day-ahead and long-term planning of system 

adequacy (i.e., meeting the system peak load during the year). Wind energy is more predictable 

in the hour-ahead time frame, but even then, the uncertainty in wind forecasts can be significant 

and must be accounted for in utility operation and dispatching.

In order to minimize impacts and maximize benefits, each utility or balancing area2 (BA) that

incorporates wind energy must learn how to accommodate its uncertainty and variability in 

operational and planning practices, and to do so while maintaining system reliability. A system 

that includes hydropower in its pool of generating resources may be well suited to accommodate 

wind energy due to hydropower’s inherent flexibility. That said, hydropower also possesses 

different operating characteristics that warrant special consideration, as compared to flexible 

thermal generation resources (e.g., simple cycle gas turbines, combined cycle gas turbines). For 

example, run-of-the-river hydropower must be used or spilled3

 2 A balancing area here refers to be a subset of the broader interconnected transmission system for which a single 

transmission system operator or balancing area authority is responsible for maintaining grid safety and reliability 

standards.

at times when the water is 

naturally flowing, limiting its flexibility. Alternatively, hydropower facilities with large 

reservoirs may allow considerable discretion in regard to when water is released, providing 

significant flexibility. On river systems with multiple hydropower facilities, water releases at an 

upstream dam will likely influence and constrain the water releases and power generation at the 

downstream dams. This interaction on a river system—especially for one in which multiple 

3 Spill refers to water that is passed through a hydropower facility but not used for power generation. Frequently this 

water passes over or through the spillway on a dam.
IEA Wind Task 24 Final Report, Vol. 1

3

owners or operators are involved—may require joint planning and the development of complex 

operating practices that will permit some form of optimal, coordinated operation between the 

facilities, or at least fair operation.

Given the background and due to the potential for synergistic operation of wind and hydropower 

facilities within or across balancing areas, and because considering the unique operating 

constraints and complexities prevalent with hydropower, utilities and researchers from several 

countries expressed interest in investigating “wind and hydropower integration” through broad 

collaboration and information sharing. In November 2003, the IEA Wind Implementing 

Agreement (IA) convened Topical Expert Meeting #41 on the “Integration of Wind and 

Hydropower Systems” in Portland, Oregon, U.S.. As a result of this meeting, a proposal was 

introduced for IEA Wind to form an “Annex” or “Task” to foster international collaboration in 

studying the potential for integrating wind power in electrical systems with hydropower. In May 

of 2004, IEA Wind established R&D Task 24, “Integration of Wind and Hydropower Systems.” 

The member countries, contracting parties, and participating organizations in the Task are listed 

in Table 3.

Integration of wind power into power systems is an active area of research. There are 

organizations devoted to its study (e.g., see www.uwig.com or 

www.windintegrationworkshop.org), and there have been numerous publications related to the 

topic including some produced by the IEA (e.g., IEA 2005, IEA 2008a, Holttinen et al. 2008). 

IEA Wind established another R&D work task in 2005, Task 25 on the “Design and Operation of 

Power Systems with Large Amounts of Wind Power,” which deals specifically with issues 

related to wind integration impacts, costs, and analysis techniques. Tasks 24 and 25 bear many 

similarities centered on wind integration, but Task 24 focused on electrical systems with 

hydropower. The goal in conducting the collaboration established in Task 24 was to study wind 

integration in a variety of electrical system configurations (load, generation, and transmission); 

hydro system configurations and characteristics; and market and operational configurations—all 

of which is more than could be studied by any one country alone—and to understand the 

potential for and limiting factors in integrating wind into systems with hydropower. 

The remaining sections of this chapter will describe aspects of electrical system planning and 

operation of relevance to wind integration; describe what is meant by wind and hydro integration 

in the context of this task; list the specific objectives of Task 24 along with the means to achieve 

these objectives; and provide an overview of the Task 24 final report, which is organized into 

two volumes. 
IEA Wind Task 24 Final Report, Vol. 1

4

Table 3. Task 24 member countries, contracting parties, and participants

Country Contracting Party Participant

Australia Australia Wind Energy Association Hydro Tasmania

Canada Natural Resources Canada Natural Resources Canada

Manitoba Hydro

Hydro Québec

Finland TEKES National Technology Agency, Finland VTT 

Norway Norwegian Water Resources and Energy 

Directorate

SINTEF Energy Research

Statkraft Energy

Sweden Swedish Energy Agency KTH Swedish Institute of Technology

Switzerland Swiss Federal Office of Energy EW Ursern

United States U.S. Department of Energy National Renewable Energy Laboratory

Grant County Public Utility District 

Sacramento Municipal Utility District

Northern Arizona University

1.1 Electric Utilities and System Operation

The purpose of the information provided here is to provide a description of electrical system 

planning and operation that is generally applicable, but independent of any particular system. 

From this foundation, the specific issues of importance to wind integration in systems with 

hydropower will be highlighted, laying the foundation for the specific goals of Task 24. 

1.1.1 Electric Utilities and Markets

Electrical power to homes, businesses, and industry is typically provided by an “electric utility.” 

Electric utilities were typically established as vertically integrated, isolated systems, responsible 

for generation, transmission, and distribution of the electricity, often through a state-regulated 

monopoly. As time progressed and the transmission system expanded, creating stronger, highvoltage connections between the various utilities, cooperation among the utilities increased and 

eventually resulted in the formation of organizations that permit sharing of certain reliability 

requirements such as contingency reserves (e.g., power pools). Through cooperation, utilities 

could gain the benefits that result from aggregating load and resources. More recently, over the 

past two decades, operation of utility systems has been evolving into market-based systems with 

many independent organizations where significant amounts of energy are bought and sold over 

large, high-voltage, interconnected transmission systems. Both types of systems exist throughout 

IEA countries, including systems that are some combination of each. Examples of wellfunctioning energy markets are the “NordPool” in the Nordic countries; the Australian Energy 

Market Operator (AEMO, formerly the National Electricity Market) in Australia; and the 

Midwest System Independent Operator (MISO) in the Midwestern United States. An illustration 

of Regional Transmission Organizations (RTOs) in Canada and the United States where 

electricity markets are operated is provided in Figure 3. Vertically integrated utilities are also 

prevalent, although the transmission and generation arms of these utilities are now normally split 

into two separate but dependent companies. Examples include the Grant County Public Utility

District (PUD) and the Arizona Public Service Company in the Western United States, and 
IEA Wind Task 24 Final Report, Vol. 1

5

Hydro Québec in the Québec Province of Canada. These utilities typically transact with other 

utilities or electric services providers via bilateral agreements, many of which are long-term, and 

in some cases through participation in neighboring market systems (e.g., Manitoba Hydro’s 

participation in MISO). Regardless of the organizational and economic structure, the basic 

function is the same: the customers purchase electricity, and it is the responsibility of those 

entities involved in operating the electrical system to plan for and provide affordable and reliable 

electricity services. In all cases, a TSO or balancing area authority is responsible for balancing 

the instantaneous aggregation of customer requests for electricity (i.e., the load) with the

available generation and transmission resources while maintaining the safety and reliability of 

the electrical grid. Generally, some type of regulatory body generally overlays the 

TSO/utility/electricity market—typically, this is done at the national level to create and 

implement the rules concerning safe, reliable, fair, and efficient operation of the electric system. 

Figure 3. An illustration of the many regional transmission organizations that have arisen in 

Canada and the United States (Source: www.ferc.gov/industries/electric/indus-act/rto/rto-map.asp)

1.1.2 Ancillary Services for Power System Reliability, Security, and Power 

Quality

Electrical generation resources, to a large degree, are planned for well ahead of time: months to 

years based on the expected magnitude and temporal patterns of customer load. The load, though 

predictable and varying in expected ways, possesses an unpredictable component based on 

customer preferences and requirements; meteorological conditions (e.g., heating or cooling);

market conditions; unforced outages of generators; etc. Therefore, TSOs have been built to 

accommodate the uncertainty and variability of load through use of “reserves” that are generally 

flexible generation resources that can ramp/start/stop quickly or through market or operational 

flexibilities (e.g., frequent scheduling intervals).

Interconnected power systems are large and extremely complex machines. The mechanisms 

responsible for their control must continually adjust the supply of electric energy to meet the 

combined and ever-changing electric demand of the system users. There are a host of constraints 
IEA Wind Task 24 Final Report, Vol. 1

6

and objectives that govern how this is done. In total, however, those actions must result in the 

following:

• Keeping voltage at each node (a point where two or more system elements—lines, 

transformers, loads, generators, etc.—connect) of the system within prescribed limits

• Regulating the frequency (the steady electrical speed at which all generators in the system are 

rotating) of the system to keep all generating units in synchronism

• Maintaining the system in a state where it is able to withstand and recover from unplanned 

failures or losses of major elements

Ancillary services is the term generally used to describe the actions and functions related to the 

operation of a balancing area within an interconnected electric power system necessary for 

maintaining performance and reliability. While there is no universal agreement on the number or 

specific definition of these services or the names for them, the following list generally 

encompasses the range of technical aspects that must be considered for reliable operation of the 

system:

• Regulation or Primary Reserve (Operational Reserve): The process of maintaining system 

frequency by adjusting certain generating units in response to fast fluctuations in the total 

system load

• Load Following or Secondary Reserve (Operational Reserve): Ramping generation up (in the 

morning) or down (late in the day) in response to the daily load patterns

• Frequency-Responding Spinning Reserve (Capacity/Contingency Reserve): Maintaining an 

adequate supply of generating capacity (usually online, synchronized to the grid) that is able 

to quickly respond to the loss of a major transmission network element or another generating 

unit

• Supplemental Reserve, 10-Minute Reserve, 30-Minute Reserve (Capacity/Contingency 

Reserve): Managing an additional back-up supply of generating capacity that can be brought 

online relatively quickly to serve load in case of the unplanned loss of operating generation

• Voltage Regulation and Volt-Amp-Reactive (VAR)4

In this list, the reserves denoted as Operational Reserve are expected to be used on a daily basis 

to cover the variability of the system load and errors in its prediction, while the 

Capacity/Contingency reserves are allocated to cover failures in the electrical system, such as 

loss of the single largest generating unit or transmission linkage. 

Dispatch: Deploying devices capable of 

controlling reactive power to manage voltages at all points in the network.

 4 Electric machinery requires two components of current to operate: power-producing current and magnetizing 

current. Power-producing or working current is current that is converted by the equipment into work. The unit of 

measurement of active power is the Watt. Magnetizing current, also known as reactive current, is the current

required to produce the flux necessary to the operation of electromagnetic devices. Without magnetizing current, 

energy could not flow through the core of a transformer or across the air gap of an induction motor. The unit of 

measurement of reactive power is the VAR. Management of reactive power is the primary mechanism for 

controlling voltage at points within the network. System operators dispatch various devices capable of producing 

reactive power, including generators, shunt capacitor banks, static VAR compensators, etc., to control voltages in 

response to continually varying customer demand.
IEA Wind Task 24 Final Report, Vol. 1

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Table 4 compares the terminology used in describing reserves/ancillary services in Australia, 

Canada, Germany, Ireland, the Nordic system, and the United States. These ancillary services are 

critical for maintaining the reliability and security of the electric grid. For any foreseeable 

combination of equipment failures or miss-operation, operating generating units must remain 

synchronized to prevent cascading equipment outages and subsequent blackouts. Figure 4 depicts

a conceptual view of these ancillary services and their associated time frames, as relevant in 

North America. In this figure, Scheduling and Unit Commitment refer to the act of optimally 

planning generation resources and reserves ahead of the actual hour of operation, which must 

occur based on forecasted data on system load (as well as wind power, unit availability, 

hydropower, etc.).

Time (hour of day)

0 4 8 12 16 20 24

System Load (MW)

seconds to minutes

Regulation

tens of minutes to hours

Load

Following

day

Scheduling

Figure 4. Time scales of importance when considering ancillary service impacts of integrating 

wind energy in the power system (Source: National Renewable Energy Laboratory)

Historically, a single entity had complete autonomy over operation of the generation and 

transmission assets in a service territory and the responsibility for operating them in a manner to 

achieve high reliability at the lowest cost. Ancillary services are tools for achieving these goals.

With the deregulation of the wholesale electric power industry, the institutional responsibility for 

some of these functions has been reallocated to RTOs, TSOs, or other similar organizations.

However, the technical reality has not changed in that these services must still be provided 

somehow, some way, by someone.

The implementation of competitive markets for ancillary services is in its relative infancy and is 

not uniform from country to country, or even within single countries. The emergence of market 

competition, in any form, has changed many of the procedures and processes for power system 

control and operation. Bidding supply into markets for the next hour or next day has replaced the 

historical top-down decision-making process used to commit and schedule generating units. Spot 

markets have supplanted some bi-lateral agreements between neighboring utilities for 

exchanging economic energy on short notices. In some locales, planning for the appropriate level 

of reserve supply is now the function of capacity markets. 

Days

Unit

Commitment
IEA Wind Task 24 Final Report, Vol. 1

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1.1.3 How Ancillary Services are Provided

Meeting the operational objectives for the power system is accomplished through coordinated 

control of individual generators as well as the transmission network itself and associated 

auxiliary equipment such as shunt capacitor banks. How individual plants are deployed and 

scheduled is primarily a function of economics. Historically, vertically integrated electric utilities 

would schedule their generating assets to minimize their total production costs for the forecast 

load while observing any constraints on the operation of the generating units in their fleet. In 

bulk power markets, competitive bidding either partially or wholly supplants the top-down 

optimization performed by vertically integrated utilities. In either case, the economics of unit 

power production have the primary influence on how a plant is scheduled. In addition, the entity 

responsible for the operation of the balancing area—an individual utility, TSO, or RTO, for 

example—must manage some generating units to regulate frequency and control power 

exchanges in real time, to make up discrepancies between actual and forecast loads, and provide 

adequate reserves to cover an unexpected loss of supply. 
IEA Wind Task 24 Final Report, Vol. 1

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Table 4. Types of operational reserves employed by TSOs in planning for balancing load and 

generation for three time scales of relevance (Source: adapted from IEA 2005)

The efficiency of thermal generating units typically varies with loading, so for each unit there is 

a point at which the cost of energy produced will be at a minimum. For large, fossil-fired and 

 5 In Australia, all reserves are called Frequency Control Ancillary Services (FCAS). All FCAS services are 

commodities on the market subject to 5 minutes dispatch. After a contingency, all FCAS reserves need to be 

restored within half an hour.

Fast Responding 

Reserve 

(seconds)

Medium-Term Reserve (intrahour)

Long-Term 

Reserve (hours 

to days) 

Australia

Contingency 

reserves 

(Frequency Control 

Ancillary Services5

Fast 6 seconds 

reserve for both 

raise and lower 

service;

)

Also regulation 

FCAS service as 

part of AGC

Slow 60 

seconds reserve 

for both raise 

and lower 

service

Contingency 

reserve; 

Delayed service 

available in 5 

minutes

N/A

Canada: 

Québec

Regulation horizon: 

1 minute with 1- to 

5-seconds

(No specific reserve defined: HydroQuébec’s system is 95% hydropower, 

which easily provides load-following 

capacities) 

Balancing reserve 

for load forecast 

and wind forecast 

uncertainties, and 

risk of outage: 1 to 

48 hours

Germany 

Primary reserve: 

available within 30 

seconds, released 

by TSO 

Secondary 

reserve: 

available within 

5 minutes, 

released by 

TSO 

Minute reserve: 

available within 15 

minutes, called by 

TSO from supplier 

N/A

Nordpool: 

Denmark, 

Finland, 

Norway, 

Sweden

Primary reserve: 

activated 

automatically by 

designated 

generators in every 

country

Nordic Regulating 

Power Market –

bids activated in 10 

minutes, from the 

country having 

cheapest bid in list

Some TSOs 

contract some 

capacity that can 

be activated during 

winter high load 

periods

Ireland Primary operating 

reserve: available 

within 15 seconds 

(inertial response/ 

fast response) 

Secondary 

operating 

reserve: 

operates over 

timeframe of 

15–90 seconds 

Tertiary response: 

from 90 seconds 

onwards (dynamic 

or static reserve) N/A

United 

States 

Regulation horizon: 

1 minute to 1 hour 

with 1- to 5-second

increments

Load-following horizons: 1 hour with 5-

to 10-minute increments (intra-hour) 

and several hours (inter-hour) 

Unit-commitment 

horizon: 1 day to 1 

week with 1-hour 

time increments 
IEA Wind Task 24 Final Report, Vol. 1

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nuclear generating units, the cost of generation generally declines with increasing loading up to 

rated output. As a result, the economics dictate that these units should be “base loaded” for as 

many hours as possible when in operation.

6

Against these operating constraints for certain units, other generating resources are deployed and 

scheduled to not only produce electric energy but also to provide the flexibility required by the 

operators to regulate system frequency, follow the aggregate system load as it trends up in the 

morning and down late in the day, and provide reserve capacity in the case of a generating unit 

or tie line failure. Some of these functions are under the auspices of a central, hierarchical control 

system generally referred to as the AGC. Others are the result of human intervention by the 

balancing area operators. In either case, the generating units participating in the system control 

activities must do the following:

Other factors, such as thermal system time constants 

or mechanical and thermal stresses, may also result in certain units being loaded at fairly 

constant levels while online.

• Be responsive to commands issued by the balancing area energy management system, 

otherwise known as “being on AGC”—participating in AGC generally requires a specific 

infrastructure for communications with the control center, the Supervisory Control and Data 

Acquisition system

• Operate such that there is the appropriate “head room” to increase generation or “foot room”

to reduce generation without violating minimum loading limits if commanded by the system 

operator or energy management system

• Be able to change output (move up or down, or “ramp”) quickly enough to provide the 

required system regulation or load following

As the electric power industry evolves, it is increasingly likely that third-party generators will 

play a large role in balancing area operations through various mechanisms and markets for 

ancillary services. One such mechanism is the short-term imbalance market, sometimes 

conducted on an interval as short as 5 minutes, during which generators bid to help the control 

area operators make up for real-time mismatches between control area supply and demand. In 

lieu of an imbalance market, utilities must arrange ahead of the hour for adequate short-term 

reserves to be online and available during the hour of operation. 

1.1.4 Time Frames of System Planning 

Within the year of operation, power system planning and operation occurs in two general time 

frames: planning up to the hour of operation and real-time operations within the hour. Some 

accounting then occurs after the hour of operation to rectify the system plan with actual 

operation. The up-to-the-hour planning is often divided into “day-ahead” and “hour-ahead” 

planning. For day-ahead planning, system operators or load-serving entities perform an 

economic optimization to commit units or secure energy via the market in an effort to minimize 

operating costs. This commitment process is based on load estimates for the following day. To 

the extent that the load estimates will be inaccurate, typically within 1% to 2%, additional and 

 6

The term base loaded is generally used to describe the operation of large generating units with high capital and 

operating costs but low fuel costs that are loaded to near maximum capability for most of the hours they are in 

service. In traditional electric utility system planning, the base load is sometimes defined as the minimum hourly 

system demand over the course of a year.
IEA Wind Task 24 Final Report, Vol. 1

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unnecessary generation and reserves will be procured, leading to a sub-optimal commitment of 

units (e.g., generators running off their peak efficiency points, unnecessarily started) and 

increased operation costs. Units are frequently rescheduled and recommitted as the operating 

hour approaches and as load estimates become more accurate. However, even at the hour-ahead 

time frame, there is still load uncertainty and therefore sub-optimal commitment. The costs that 

are incurred in system operation resulting from uncertainty in forecasting and the resulting suboptimal commitment are sometimes referred to as unit commitment costs.

The exact timing and mechanism in which generation units are committed differs from one 

balancing area to another, and depends on whether or not markets exist for trading power and 

ancillary services. Figure 5 shows a timeline of actions in Grant County PUD’s generation 

planning activities. As illustrated, the plan for Day 3 is set on Day 1, but can be modified on 

Day 2 up to 18 hours before the beginning of Day 3. After this point, any further transactions 

typically occur during the day of operation as an hour-ahead transaction. In understanding the 

timing of transactions for Grant PUD, it is important to recognize that Grant County PUD is a 

relatively small utility (with less than 1,000 MW of peak load) and that it functions most similar 

to a vertically integrated utility with purchases and sales occurring through bilateral transactions.

Another timeline for planning actions is shown in Figure 6 for the Nordel market. In this system, 

the spot market closes 12 hours before the day of operation. The Elbas market is an intra-day 

market to cover anticipated imbalances between the load and generation, and transactions on this 

market can be made up until 1 hour before the delivery hour. In both the Nordel market and the 

trading system in which Grant County PUD operates, there is no real intra-hour market, and the 

TSOs must plan for and acquire sufficient reserves an hour ahead for the hour of operation.

12 am noon 4 pm 12 am 6 am 10 

pm

Day 1 Day 2 Day 3

Schedule 

plan set for 

Day 3

Modifications & 

purchases/sales 

made for 

schedule set for 

Day 3

Real-Time 

operations 

during the hour 

of operation

LLH HLH LLH

12 am 6 am 12 

am

Hours 

ahead up to 

hour ahead 

transactions

Figure 5. Typical time frame for planning operations at the Grant County PUD in the United States 

(Source: adapted from Acker et al. 2007)

Day before delivery Day of delivery Day after delivery

12:00 15:00

Spot market 

closes

Delivery 

hour

Regulation during 

hour

Bids to regulating 

market

Elbas 12:00

Balance 

settlement

for previous day

Figure 6. Timeline for day ahead, hour(s) ahead, and real-time planning operations for the Nordel 

system (Source: M. Olsson presentation, Task 24 R&D Meeting #2, Launceston, Tasmania 2006)
IEA Wind Task 24 Final Report, Vol. 1

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1.1.5 System Resource Adequacy

Beyond the reserves employed within the weekly time frame, utilities also engage in long-term 

capacity planning to ensure system resource adequacy. This level of planning is focused on 

guaranteeing sufficient generation is available to meet anticipated load in future years, especially 

the load during peak hours and months. The contribution of wind energy toward system planning 

is carried out using the standard methods that apply to any generator; for example, employing the 

loss of load probability for a generator or wind power plant and computing its effective load 

carrying capacity (ELCC) (see Milligan and Porter [2008]). To determine an accurate number for

the ELCC, multiple years of data is desirable. A similar calculation is made for hydropower, and 

is dependent on the expected precipitation levels combined with existing hydrological and 

reservoir information, and generally changes from year to year. The amount of capacity that a 

given wind power plant can provide is often referred to as its capacity credit or capacity value, 

typically stated as a percentage of its nameplate capacity.

1.2 What is “Wind and Hydropower Integration”? 

For the purpose of this research task, wind and hydropower integration refers to the study of 

wind integration into systems with hydropower, or more specifically, conventional hydropower 

plants (versus pumped hydropower). Wind and hydropower are both variable and uncertain over 

time frames of relevance for system planners: wind power varies within minutes and across

seasons but is reasonably stable from year-to-year; whereas hydropower is typically highly 

predictable in time frames less than a couple of months to a year, but varies more from year-toyear as precipitation levels changes. As a mature technology, planning for long-term variations 

in hydropower is a common part of utility planning. Wind power, however, exhibits variations 

significant on the shorter timescales of utility operation and is commonly treated as a negative 

load in the system.7 As will be explained later in this report, wind power will increase the overall 

variability and uncertainty that must be dealt with in a balancing area, thus increasing the 

system-wide need for reserves and ancillary services that were described earlier. This is 

especially true as wind penetration8

• Run-of-river with very little water storage for which power generation is directly related to 

the natural inflow. With meteorological prediction, natural inflow forecast is normally used 

to predict the output, although there typically is still a low level of control up to a few hours 

depending of the capacity of the reservoir.

climbs to appreciable levels (e.g., 5% to 10%; see IEA 

2005). With respect to hydropower flexibility, there are essentially three different configurations:

• Hydropower plants with reservoirs in two configurations:

o Run-of-river type power plants with some storage, but in a cascade with one large 

reservoir upstream. In this case, with an upstream outflow prescribed, there is a relatively

low level of flexibility at the power plant (perhaps a few hours to tens of hours)

o A cascade of large reservoirs and power plants with more flexibility where power output 

is completely independent of the natural inflow pattern.

 7 A more in-depth discussion of the treatment of wind power as negative load is provided in Volume 2, Chapter 1. 8 Wind penetration is defined here as the installed capacity of wind power divided by the annual peak system load. 

Other relevant methods of defining the wind penetration are presented and discussed in Volume 2, Chapter 1 of the 

Task 24 Final Report.
IEA Wind Task 24 Final Report, Vol. 1

13

These three configurations have different levels of flexibility, and all have some flexibility to 

control their power output. In any case, due to its short-term flexibility and rapidly responding 

generators, hydropower can help address the challenges created by wind power through 

provision of ancillary services or via energy storage, and in doing so may benefit economically 

through a high-value use of its resource. 

Since the introduction of wind power in a BA will increase the need for ancillary services, it will

potentially change production patterns at hydropower facilities that either choose to provide 

these services or are required to do so. Due to differences in hydro systems, it is not obvious that 

deploying hydropower flexibility to accommodate enhanced ancillary service requirements will 

necessarily result in increased revenues for the hydropower operators or decreased system 

operating costs, though it certainly can. Moreover, due to the wide variety of balancing areas 

authorities or TSOs, electric markets or lack thereof, system load, generation and wind power 

characteristics, and the variation in hydropower systems themselves, it is not clear the extent to 

which wind power and hydropower can complement one another in any given BA, nor is it clear 

whether or not the experiences of wind and hydropower integration in one BA will apply to 

another. For example, a BA in need of new generation can benefit by building new wind power 

resources. Effectively using the hydropower resources available in this BA to help manage the 

enhanced variability and uncertainty introduced by wind power may lead to a low-cost, lowcarbon solution for generation expansion. Alternatively, if wind power is required via political 

mandate in a BA where no new generation resources are required to cover load growth or for 

export opportunities, then wind power may not lead to decreased system operating costs (perhaps 

as would be the case for any new generation that is not required for meeting load). Furthermore, 

hydropower systems such as those in the United States often serve many purposes in addition to 

providing electrical power, some of which have a higher priority than power generation. 

Understanding how wind will impact other hydro operations and priorities that may exist, such 

as compliance with environmental regulations, irrigation water deliveries, flood control, etc., is 

important for TSOs and system operators that plan to incorporate wind power. 

To summarize, this study of wind and hydropower is focused on wind integration into power 

systems with hydropower. While there are numerous issues to address in this study, they are all 

related to answering the following basic questions: 

• Grid Integration Impacts and Costs: What is the impact of wind power on the power system 

balancing area, and specifically, the ancillary services/reserves required; long-term system 

planning (capacity value); and transmission system (e.g., scheduling bottlenecks)? What are 

the appropriate study methods?

• Hydropower Impacts: What impact will provision of these ancillary services have on the 

hydropower system? Impacts include those on the physical resources (e.g., operations and 

maintenance); operational flexibility; and hydro system priorities (e.g., meeting flow 

constraints, satisfying environmental regulations).

• Economics: What is the overall economic value of wind energy in the hydro system? What 

“opportunity costs” are incurred for the hydro system in providing ancillary services to wind 

power (thus not being available for scheduling), and what are the economic

benefits/opportunities in doing so? What is the effect of market configurations and system 
IEA Wind Task 24 Final Report, Vol. 1

14

operation (e.g., scheduling intervals)? Are there wind/hydro “products” that can be of value 

both to power customers and hydropower providers (e.g., energy storage and redelivery)?

• System Configuration: Based upon the answers to the questions above, what are practical 

configurations for integrating wind and hydropower?

Building upon these basic questions, Section 1.3 addresses the specific objectives of Task 24 

along with the means to achieve those objectives.

1.3 Task 24 Objectives and Means to Achieve

The primary purposes of Task 24 are to conduct cooperative research concerning the generation, 

transmission, and economics of integrating wind and hydropower systems, and to provide a 

forum for information exchange. Task 24’s specific objectives are a follows:

• Establish an international forum for exchange of knowledge, ideas, and experiences related to 

the integration of wind and hydropower technologies within electricity supply systems.

• As it pertains to wind and hydropower integration, share information among participating 

members concerning grid integration, transmission issues, hydrological and hydropower 

impacts, markets and economics, and simplified modeling techniques.

• Through information sharing and exchange of ideas, identify technically and economically 

feasible system configurations for integrating wind and hydropower, including the effects of 

market structure on wind-hydro system economics with the intention of identifying the most 

effective market structures.

• Document case studies pertaining to wind and hydropower integration, and create an online 

library of reports.

To achieve these objectives, Task 24 relies on the research efforts within member countries 

related to integration of wind power and hydropower resources within an electricity supply 

system. An initial kick-off meeting was held in February 2005 to discuss the research and case 

studies to be undertaken, their related task objectives, and a consistent framework for problem 

formulation and results presentation. Five R&D meetings were held over the next 3 years 

following this initial meeting. The case studies conducted by the country participants were 

organized into three primary contexts: grid integration, hydro system impacts, and the electricity 

market and economics. The means to achieve the objectives was through the case studies listed 

in Section 1.3.1 to 1.3.4.

1.3.1 Grid Integration Case Studies

When considering wind power and hydropower integration, the first context to consider is that of 

the electrical transmission grid, whether that be an isolated grid serving an island community or a 

geographically large grid that spans a significant fraction of a continent. A large transmission 

grid is typically broken into several smaller transmission balancing areas in which reliability 

requirements are met while balancing loads with generation. Within any given balancing area,

there may be several different types of generators, including natural gas turbines, coal-fired 

steam plants, nuclear power, hydropower, wind energy, and perhaps others. The average load 

within a control area typically varies in predictable daily and seasonal patterns, but also contains 

an unpredictable component due to random load variations (due to customers randomly starting 
IEA Wind Task 24 Final Report, Vol. 1

15

and stopping electrical loads) as well as unforeseen events. As described previously, in order to 

compensate for these variations and unforeseen events, steps are taken to ensure system 

reliability by having additional generation capacity online to provide regulation (for the random 

load fluctuations) or set aside as reserves (to account for load forecast errors, unforeseen events, 

and unplanned outages)—in other words, through the provision of ancillary services. The 

generators within an electrical system each have their own operating characteristics. Some 

generators, such as coal-fired plants, primarily provide for base load and serve the slower daily 

variations in load. These generators are relatively slow to respond to load changes and have 

extended start-up and shut-down periods. Other generators, such as combustion turbines or hydro 

generators, are quick to respond to fluctuations, and can be started quickly. These more agile 

generators are the type used to provide regulation and load following on an hourly basis. The 

ability to provide ancillary services is of economic value to a generator above and beyond the 

energy produced while operating.

Introducing wind generation into a control area can increase the regulation burden and the need 

for reserves, due to its natural variability. However, since the control area has a constantly 

varying load, the impact of the wind plant variability imposed on the load variability may range 

from negligible to significant depending on the level of penetration and variability of the wind 

resource. Therefore, in order to accurately determine the impact on the control area reliability 

and the consequential incremental increase in need for ancillary services, the wind generation 

must be analyzed in the context of the transmission grid, fully encumbered with all of its loads, 

generators, and their corresponding characteristics.

Determination of the ancillary services imposed by wind integration on a grid is the first 

important step in understanding the potential for integration with hydropower resources. 

Hydropower, being a responsive generation resource capable of providing ancillary services, can 

supply the incremental increase in ancillary services caused by wind energy. The natural second 

step in the process of studying wind/hydro integration is to determine the extent of the ancillary 

services that can be supplied by hydro generation located in the balancing area or elsewhere 

within the interconnected grid. Given the existence of a finite amount of hydro generation on any 

given grid, only a finite amount of wind-energy-induced variability and uncertainty can be 

supported by the hydro. However, since system balance and reliability must be maintained 

within a balancing area, it is not necessary that wind and hydro resources be co-located, but 

rather, they may be located at their optimal locations, geographically far apart from one another. 

Furthermore, to the extent that electrical energy and ancillary services can be transferred from 

one balancing area to another, the potential for integrating wind with hydro resources is only 

limited by the transmission capacity within an interconnected grid. The resources themselves 

may be located great distances apart as long as they are electrically interconnected. Diverse 

geographical distribution of wind within a control area can have advantages in smoothing the 

wind variability and increasing the amount that can be effectively integrated with hydropower.

A unique advantage of hydropower compared to other generation resources, beyond simply 

providing ancillary services, is the ability to access the built-in energy storage capabilities of 

water within hydro reservoirs. Combining the energy storage ability of a hydro reservoir with 

wind energy could be synergistic and increase the value of wind and hydropower in the energy 

supply system. Hydropower generators could benefit by providing wind generators ancillary 

services and energy storage, meanwhile facilitating integration of wind energy on the grid.
IEA Wind Task 24 Final Report, Vol. 1

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Access to transmission is another very important consideration in developing wind energy. Many 

existing transmission facilities have been built for existing hydro or thermal resources, and there 

is little or no firm transmission capacity available. This limitation, however, is frequently 

contractual and not physical. In other words, there may be ample non-firm transmission capacity 

available for wind energy that is either inaccessible or too costly. Furthermore, to the extent that 

wind plants can be located near hydropower transmission facilities, there is potential to more 

fully utilize the existing transmission facilities (since many hydro facilities have capacity factors 

significantly less that 100%). 

Given the wide variety of hydropower installations, reservoirs, operating constraints, and 

hydrologic conditions, there are many possible wind/hydro integration combinations and many 

possible solutions. Hydro generators typically have very quick start-up and response times and 

flexibility in water release timing, and therefore may be ideal for balancing the increase in 

variations induced by wind power within the context of the balancing area load. Studying grid 

integration of wind energy with hydropower lies at the heart of understanding its potential. Some 

desired outcomes of the grid integration case studies include the following:

• Identifying feasible wind/hydro system configurations; that is, investigating specific 

configurations with varying wind and hydropower characteristics, market arrangements, 

hydro constraints, balancing area characteristics, etc., and determining which are most 

practical and if some are not

• Identifying and developing techniques to analyze grid integration of wind energy, especially 

as they pertain to grids that include hydropower

• Understanding the capacity of wind energy that can be supported by hydropower in terms of 

the ancillary services

• Understanding the potential for energy storage

• Understanding the technical constraints and limiting parameters in wind power and 

hydropower integration 

1.3.2 Hydro System Impact Case Studies

The second context within which to consider wind power and hydropower integration relates to 

the impacts on hydro system operation and, in particular, the non-hydropower functions. 

Depending on the relative grid integration impacts of the wind power, integration may 

necessitate changes in the way hydropower facilities operate. These changes may impact 

operation, maintenance, revenue, water storage, and the ability of the hydro facility to meet its 

primary purposes. Additionally, there may be positive hydro system benefits derived from 

integrating with wind, such as those related to water storage and compliance to environmental 

regulations. Without a proper understanding of these and other impacts and benefits, hydro 

facility operators may be slow to embrace the opportunities found in integrating with wind 

power. Therefore, study of the impacts on hydropower facilities and hydrological operations 

directed at determining benefits, detriments, and costs will be fundamental in paving the way for 

implementation of wind/hydro projects.
IEA Wind Task 24 Final Report, Vol. 1

17

1.3.3 Market and Economic Case Studies

While grid integration and hydro system impact studies may demonstrate the technical feasibility 

to integrate wind power and hydropower systems, practical implementation will depend on the 

economic feasibility of a given project. This in turn will depend on the organization and 

characteristics of the electric power system, the load being served, interconnections with 

neighboring systems, and the type of electricity market in which the wind-hydro integration 

project is considered. Thus, the third context within which to consider wind/hydro integration is 

market and economics. Addressing economic feasibility in the context of the electric market 

characteristics will provide insight into which market types wind/hydro integration will be 

practical, as well as the key factors driving the economics. Additionally, to the extent that the 

organizational rules regarding scheduling and pricing of electricity are not constrained by 

physical generation and transmission facilities, there is opportunity to devise new methods of 

scheduling and pricing that will be advantageous to wind/hydro integration and permit better use

of system resources. These case studies will address the effects of market structure on 

wind/hydro system economics with intent to identify the most effective market structures. 

1.3.4 Simplified Modeling of Wind-Hydro Integration Potential

Based on characteristics of the local transmission balancing area loads, hydropower facilities, 

and wind power resource, simplified methods for approximating the amount of wind power that 

can be physically or economically integrated with existing hydropower should be devised. The 

analysis methods should include only the most influential hydro operational constraints and 

electric reliability concerns. The goal of this modeling objective is to provide a realistic 

technique for approximation of the potential magnitude for integrating wind power and 

hydropower, without the necessity of conducting an in-depth study. Simplified methods must 

still consider a “system-wide” perspective, with the understanding that wind power and 

hydropower interact within a larger grid that includes other generation resources. Because of 

this, it may be more fruitful for some investigators to consider simplified methods that study how 

much wind can be integrated in a large interconnected grid that includes significant hydropower 

resources, but not to consider specific hydropower resources.

1.3.5 Results Expected

Because the collective research of Task 24 relied on existing efforts within the member 

countries, all members did not address all case study contexts mentioned above.

9 However, one 

of the task objectives was information exchange among collaborators so that every participant 

had the opportunity to evaluate and comment on all case studies, including problem formulation 

and assumptions, analysis techniques, and results. This interaction is a key benefit of the IEA 

R&D tasks and fosters a collaborative environment that permits the substantial research 

capabilities in each country to more thoroughly address important and broad topics, beyond what 

they could do themselves. A complete list of the results expected upon formation of the task is 

presented below10

 9 See Chapter 1 of Volume 2 for a table summarizing the research efforts and case study topics addressed by each 

member country.

:

10 This list been taken directly from Article 4 of the Task 24 proposal “Results Expected.” 
IEA Wind Task 24 Final Report, Vol. 1

18

• Establish the technical and economic feasibility of integrating wind and hydropower systems 

in specific case studies that provide required power quality and dependability, and meet 

market criteria.

• Identify practical wind/hydro system configurations.

• Formulate a consistent method of studying and comparing the technical and economic 

feasibility of integrating wind power and hydropower systems.

• Determine the ancillary services required by wind energy, and the electric system reliability 

impacts of incorporating various levels of wind energy into utility grids that include hydro 

generation, including investigating the range of values for hydropower energy storage and 

other ancillary services, based on market opportunities and costs of wind integration, and 

including direct costs to the hydropower assets.

• Establish an understanding of the issues, costs, benefits, challenges, and opportunities 

directly related to integrating wind power and hydropower systems and the best ways to 

manage them.

• Develop guidelines for evaluating and comparing environmental and social impacts from 

hydropower, wind power, and transmission/distribution assets and systems.

• Investigate enhancing the flexibility of power planning through simulation of reservoir 

operation, selecting optimum configurations for specific sites and wind/hydrologic 

forecasting.

• Create a database of reports describing case studies and wind/hydro system analyses 

conducted through cooperative research of Task 24.

1.4 Report Organization

This final report of Task 24 has been organized into two volumes. The first volume provides the 

background necessary to understand the work undertaken by the task and the main results. The 

second volume focuses on the study methods employed and provides a thorough description of 

the case study projects and the results from each that are of relevance to the task. 

The purpose of this introductory chapter was to provide the background necessary to understand 

the reasons for forming Task 24 and to present the member countries and organizations. The 

salient aspects of electrical system operation and planning were then described in order to lay the 

foundation upon which the results of the task are based. With this information in place, the 

meaning of “wind and hydropower integration” was defined followed by the objectives of the 

task and the means of achieving them. Chapters 2 and 3 provide an overview of wind power and 

hydropower, respectively, discussing the aspects of importance to Task 24 objectives and 

expected results. Chapter 4 describes power system operation and balancing in systems with 

wind power and hydropower, drawing upon the case studies and other relevant literature. 

Conclusions of the task and suggested future directions for the study are addressed in Chapter 5.
IEA Wind Task 24 Final Report, Vol. 1

19

2 Wind Energy Overview

As the amount of wind power on the grid has grown to substantial amounts, large wind power 

plants have arisen ranging in size from 50 MW to on the order of several hundred megawatts. 

While less than 50 MW of smaller wind power installations may feed into the utility distribution 

system, large wind power plants often feed into a high-voltage transmission system through a 

substation, and in this sense look like a typical interconnected power plant. Modern wind 

turbines now function more like mature power generation technologies: they are able to adhere to 

low-voltage ride-through standards and provide reactive power support, and models for wind 

power plant behavior have been developed for transmission system electrical power system 

simulations. However, one of the ways in which wind energy does not behave like a traditional 

power generation resource is that it is not dispatchable (except for possibly shutting down 

operating turbines to shed generation), and there is significant uncertainty in its prediction. 

Electric energy production from a large wind generation facility over a period of time—months, 

years, or the life of the project—can be estimated accurately enough to secure financing for the 

large amount of capital necessary to construct the facility. Over shorter time frames, however, 

production is less predictable. One of the most significant barriers to further development of 

wind generation stems from the fact that the processes and procedures for the design, planning, 

and operating of large interconnected utility systems are necessarily biased toward resource 

capacity (the rate of energy transfer to the grid, not the amount delivered over a longer period of 

time) to ensure the adequacy, reliability, and security of the electric supply for all end-users.

Integrating large amounts of wind energy into the larger portfolio of electric generation resources 

requires some special considerations on the part of those charged with operating the electric 

system. Substantial amounts of wind generation in a utility system will increase the demand for 

the various ancillary services described in the previous chapter. The ability of and cost to the 

balancing area to provide the required level of these services for successful integration depends 

on the makeup of its generating fleet, agreements with neighboring balancing areas, and the 

existence of competitive markets for such services. 

Chapter 4 of this report will address the impacts and costs of wind integration as investigated in 

the case studies performed for Task 24. The purpose of this chapter is to describe the salient 

aspects of wind energy relative to electrical system planning and operation, and in particular will 

describe the “value” of wind energy and the characteristics of wind power’s variability and 

uncertainty in its prediction. 

2.1 The Value of Wind Energy

An overall perspective on the value of incorporating wind energy into a utility system is shown 

in Figure 7. The green bar shown represents the cumulative positive financial benefits of wind 

energy accrued over the course of a year, typically normalized per megawatt-hour of wind 

energy production, the largest component of which is the marginal value of the wind energy.

This marginal value is dependent upon when the wind blows and is higher during peak load 

hours and lower off-peak. It is also dependent on the market conditions, if that is relevant for a 

given utility (i.e., the utility participates in a market). Wind power also possesses a capacity 

value, as suggested in the figure. Although wind is primarily an energy resource, it will 

contribute some capacity toward the total system capacity required to meet peak system loads, 

and therefore avert the need for other capacity additions to the system. The amount of capacity 
IEA Wind Task 24 Final Report, Vol. 1

20

value attributable to wind power is addressed later in this chapter. Wind power may also be 

attributed tax credits, such as is the case in the United States, or other credits or feed-in tariffs 

that add to its value. For example, in countries where emissions are limited due to environmental 

standards and there is a tax or fee associated with carbon (or other) emissions, a value can be 

calculated for the savings in emissions that would otherwise have occurred without wind 

generation. It is possible there will be other credits associated with wind energy as represented 

on the bottom of the green bar in the figure. For example, one might consider the hedge value of 

wind energy in mitigating fuel costs risks and reducing fuel costs associated with natural gas 

purchases and associate a value to it, see Bolinger et al. (2002). On the cost side, represented by 

the red bar, the three main costs identified are the cost of wind power, the transmission costs, and 

the “integration costs.” Here, the dominant cost is the cost of wind power, and it is determined 

either by the annualized capital cost plus operations and maintenance (O&M), or it may be the 

contract price paid for the wind energy via a power purchase agreement, etc. The transmission 

costs are those costs associated with either upgrading the transmission system or building new 

transmission in order to bring the wind power to the grid. This leaves the integration costs, which 

are all those costs incurred in operating the system to accommodate the incremental variability 

and uncertainty that the wind power introduces into the system net load, above that associated 

with load alone. These additional costs are typically incurred as additional ancillary services and

reserves, and should be inclusive of increased O&M costs due to more start-ups and cycling of 

existing units. For some systems, those including hydropower in particular, there may be an 

opportunity cost associated with diverting hydro resources from their normal economic use to 

provision of ancillary services. In the context of a wind integration study where a cost production 

simulation is run (see Volume 2, Chapter 1), this cost should be captured and included as either 

an integration cost or simply in assessing the overall cost of operation. Overall, there is generally 

a net benefit due to wind energy for a wide range of wind penetration levels, represented by the 

blue “net benefit or cost” bar in Figure 7, the magnitude of which varies from system to system

based upon each system’s conventional generation resources, load, wind resources, operational 

rules and constraints, and the market within which it operates. The “other benefits” shown 

correspond to non-monetized benefits, as might be the case for avoided carbon emissions, the 

hedge value of wind, etc. 

Denny et al. (2006) present a good example of an analysis that considers the value of wind 

energy in the Irish power system. Another example wind integration study that considers the 

overall benefit of wind in a utility system is the study conducted by General Electric for the New 

York State Energy Research and Development Authority (GE Energy 2005). 
IEA Wind Task 24 Final Report, Vol. 1

21

Figure 7. Overall perspective of the value derived from integrating wind into a utility system

(Source: Acker 2007a)

2.2 Characteristics of Wind Power Variability

The characteristics of wind variability cross several time frames of power system operation and 

planning, from short, minute-to-minute fluctuation to longer-term seasonal and annual variations.

One of the key challenges in large-scale wind integration is the lack of familiarity that system 

operators have regarding the magnitude and frequency of wind power output variations, and the 

impact that will have on system operation. Because these variations affect wind and hydropower 

integration, a summary of actual wind power variations will be provided here. The bulk of what 

will be presented draws upon the work of Wan at NREL, based on wind power output data taken 

from up to 35 wind power plants spread across the United States (Wan 2004, Wan 2005, Wan 

2008).

2.2.1 Variability in the 1-Minute Time Frame

Because the 1-second changes in power output at a wind power plant tend to be quite small 

(<0.1% of installed capacity) and are uncorrelated between different power plants and even 

different turbines within a power plant (Wan 2004), the first time scale of significance to windhydropower integration is the 1-minute time frame. Variations of this resolution can impact the 

regulation required in operating the system. Figure 8 shows a distribution of 1-minute step 

changes (i.e., the difference in output from one minute to the next) at a 103.5-MW wind power 

plant over the course of 1 month. At this plant, 90% of the step changes were within 1% of

installed capacity. The ramp rates shown are computed by dividing magnitude of change during 

a ramp by its duration, normalized by the wind power plant capacity. As a consequence, there are 

fewer ramps than step changes, and their magnitudes are smaller. This type of 1-minute 

variability is typical of a single wind power plant.

Marginal value 

of wind energy

Cost of wind 

energy

“Integration” costs

Capacity value

Tax credits / Tariffs

Other credits

Combine all 

benefits and costs

Net benefit 

or cost

Other 

benefits

Transmission costs

Costs

Benefits
IEA Wind Task 24 Final Report, Vol. 1

22

Figure 8. Distribution of 1-minute step changes and ramp rates based upon 1-minute data for a 

103.5-MW wind power plant in Southwest Minnesota, U.S. (Source: Wan 2004)

Table 5 shows a statistical summary of the magnitude of 1-minute step changes at the same 

power plant depicted in Figure 8, but for 12 months of operation. As shown, while there are 

changes in behavior from month to month, the general magnitude of the changes stays the same 

throughout the year. As for the maximum and minimum 1-minute changes shown, these include 

the forced outages and maintenance outages, and are not only due to changes in the wind speed. 

The effect of aggregating the output of wind power plants on the 1-minute step changes is 

displayed in Table 6. Here, the power output from seven wind power plants spread across a large 

area11

Table 6

has been aggregated, then analyzed for the 1-minute changes. As can be seen, the average 

magnitude of step size, expressed as a percent of total capacity, is about half of what it was for 

the single 103.5 MW power plant of .

 11 Spacing between these power plants ranged from 40 to 1500 km.
IEA Wind Task 24 Final Report, Vol. 1

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Table 5. Statistical summary of the magnitude of 1-minute generation changes at a 103.5-MW wind 

power plant Minnesota, U.S. (Source: Wan 2004)

Table 6. Statistical summary of the aggregated 1-minute generation changes at seven wind power 

plants located in Minnesota, Iowa, and Texas, U.S., with a total installed capacity over 790 MW 

(Source: Wan 2004)

2.2.2 Variability in the 10-Minute Time Frame

The next time frame of significant wind power variations to be considered is the 10-minute time 

frame. Variations within this temporal interval can affect system operation, in particular the 

regulation and load following. Consistent with the previous tables presented, Table 7 and Table 8

show statistical summaries of the step changes in 10-minute average power output from a single 

103.5-MW wind power plant and an aggregate of seven wind power plants of total capacity just 

over 790 MW (Wan 2004). For a single power plant, the average magnitude of step change in the 

10-minute power output was 2.1% of total capacity, whereas it was 1.1% for the combined 

output of the seven power plants. Compared to the 1-minute changes, the 10-minute changes are 
IEA Wind Task 24 Final Report, Vol. 1

24

more significant. With respect to the effect of aggregating the output of several wind power 

plants, the magnitude of the step changes as a percent of installed capacity is reduced by about 

half. The minimum and maximum step changes shown in these tables include the forced and 

planned maintenance outages and no attempt was made to remove these from the data. Note, 

although the total capacity is about seven times greater for the output of the aggregated wind 

power plants, the minimum and maximum 10-minute changes are only roughly double that of the 

single wind power plant, demonstrating the advantageous effects of multiple and spatially 

diverse wind power plants on the overall 10-minute variability. 

Table 7. Statistical summary of step changes in the 10-minute average wind power at a 103.5-MW 

wind power plant Minnesota, U.S. (Source: Wan 2004)

Table 8. Statistical summary of the step changes in the 10-minute average wind power at seven 

wind power plants located in Minnesota, Iowa, and Texas, U.S., with a total installed capacity over 

790 MW (Source: Wan 2004)
IEA Wind Task 24 Final Report, Vol. 1

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2.2.3 Variability in the 1-Hour Time Frame

Wind power variations in the 1-hour time frame are perhaps the most significant when 

considering wind integration. The reason for this is two-fold: (1) wind power can exhibit 

significant changes over the course of 1-hour; and (2) many power systems are planned and 

generation resources committed up to the hour of operation; within the hour, the system is 

operated with the resources set forth in the hour ahead plan. For example, recall the planning 

timelines presented in Figure 5 and Figure 6. An example of the hourly step changes in average 

wind power production at a typical wind power plant is provided in Figure 9. This figure reveals 

that the preponderance of hourly changes is within ±30% of the installed plant capacity, which is 

important because it gives the system operator a sense for the variation in wind power that 

should be expected. However, system operators are responsible for maintaining reliability, and it 

is often the events (hourly changes) way out in the tails that are of most concern to them, even 

though they seldom occur. A statistical summary of the hourly step changes at this power plant is 

provided in Table 9. For the 12-month period reported, the average hourly step change was 6.5% 

of plant capacity with a standard deviation of about the same magnitude. This is about three 

times the average change of the 10-minute average wind power data. As for the monthly 

maximums of the positive and negative step changes in hourly average power, the range varies 

from 30% to 80% of plant capacity depending on the month. A similar statistical summary is 

presented in Table 10, but for the seven aggregated wind power plants mentioned previously. In 

comparison to the previous table, the beneficial effects of geographic diversity and aggregation 

are apparent: the average hourly step change is cut in half to 3.1%, and although the overall 

capacity is seven times larger than the previous table, the maximum in hourly step changes only 

approximately doubles. With respect to the maximum changes in wind power from hour to hour, 

it is of great benefit to the system operator to be able to predict these changes an hour or more 

ahead of time. Knowing when to expect these large changes to occur can help the system 

operator manage the costs addressing them.

Figure 9. Distribution of hourly step changes as a percentage of capacity for a 103.5-MW wind

power plant in Minnesota, U.S. (Source: Wan 2004)
IEA Wind Task 24 Final Report, Vol. 1

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Table 9. Statistical summary of step changes in the 1-hour average wind power at a 103.5-MW 

wind power plant in Minnesota, U.S. (Source: Wan 2004)

Table 10. Statistical summary of the step changes in the 1-hour average wind power at seven wind 

power plants located in Minnesota, Iowa, and Texas, U.S., with a total installed capacity over 

790 MW (Source: Wan 2004)

2.2.4 Variability in the Daily, Seasonal, and Yearly Time Frame

Beginning with the daily variations in wind power production, the output of a wind power plant 

can remain fairly steady or it can range anywhere from no production to full capacity. Figure 10

shows a plot of the 1-minute power data for one week from two 100-MW class wind power 

plants in the United States (Wan 2004). This figure does a good job displaying the type of daily 

variability that can occur: on the third day (hours 48 to 72) the power varies from full output, to 

no output, then back to full output; on the fifth day (hours 96 to 120), the power output remains 

high most of the day. These variations are of interest, as they provide a system operator with an 

idea of what to expect for a wind power plant. However, what is most important in determining 
IEA Wind Task 24 Final Report, Vol. 1

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the impacts of these variations is to know how these modify the load net wind that the system 

operator must deal with, and the extent to which the variations can be forecasted.

Figure 10. A 1-week trace of 1-minute power output from two wind power plants of nameplate 

capacity 103.5 MW and 113.25 MW, located 200 km apart (Source: Wan 2004)

The daily variations of a wind power plant often form a consistent pattern, or diurnal 

distribution, with the wind blowing consistently during certain times of the day based upon the 

meteorology at a given site. Figure 11 shows the diurnal distribution of wind power production at 

the 103.5-MW wind power plant in Southwest Minnesota, United States, mentioned previously 

(Wan 2004). The plot on the left side of this figure displays the diurnal pattern during the autumn 

months over four consecutive years, while the plot on the right considers the summer months. 

The daily wind patterns show a consistent trend over the years plotted, tending to have a lower 

production in the early evening. These daily patterns are site-specific and tend to vary throughout 

the year as the weather patterns shift with the changing seasons. It is important to note that there 

is significant variability around the diurnal patterns displayed. As an example, consider the plot 

in Figure 12 showing the monthly average diurnal variation from a small wind power plant 

during the month of January 2004, and the 1-minute daily power production for every day of that 

month. The bold, black line that runs approximately horizontally across the plot indicates the 

diurnal average. At this particular site, there is no diurnal pattern during the month as the winds 

were driven primarily by synoptic weather fronts and not from daily heating or cooling patterns. 

The daily traces of wind power shown in this figure give a sense for the variation that can occur 

from day to day at this wind power plant. 

The plots in Figure 13 show the monthly and seasonal variations in wind power production (Wan 

2008). Both of these plots show the monthly energy production from wind power plants in 

Southwest Minnesota (Lake Benton) or near McCamey, Texas, U.S., for several years. One thing 

to notice from these plots is that there is a consistent pattern of energy production from month to 
IEA Wind Task 24 Final Report, Vol. 1

28

month that is repeated on a yearly basis. This type of consistent seasonal pattern is very common, 

although the specific shape of it will change from site to site as one considers different locations 

across the globe. With respect to system planning and operation, when the wind power shows up 

on the system is important both with respect to its marginal value (e.g., higher during peak hours 

and peak months). 

Figure 11. Average diurnal profile of the wind power output of a 103.5-MW wind power plant over 

three months in the autumn (left) and summer (right), for four consecutive years 

(Source: Wan 2004)

Grant PUD's Portion of Nine Canyon Wind Output (1-min data)

January 2004 - All Days

-2.000

0.000

2.000

4.000

6.000

8.000

10.000

12.000

14.000

0:00 4:00 8:00 12:00 16:00 20:00

Time of day

MW request

1-Jan-04

2-Jan-04

3-Jan-04

4-Jan-04

5-Jan-04

6-Jan-04

7-Jan-04

8-Jan-04

9-Jan-04

10-Jan-04

11-Jan-04

12-Jan-04

13-Jan-04

14-Jan-04

15-Jan-04

16-Jan-04

17-Jan-04

18-Jan-04

19-Jan-04

20-Jan-04

21-Jan-04

22-Jan-04

23-Jan-04

24-Jan-04

25-Jan-04

26-Jan-04

27-Jan-04

28-Jan-04

29-Jan-04

30-Jan-04

31-Jan-04

Average

Figure 12. Plot showing the diurnal variation of output from a small wind power plant during 

January 2004 (Source: Acker et al. 2006)
IEA Wind Task 24 Final Report, Vol. 1

29

Figure 13. Monthly energy production for a single power plant (left) and for several power plants 

(right), for several years of operation (Source: Wan 2008)

One can also deduce some useful information about the year-to-year variations in wind energy 

production from the figures previously presented. Figure 11 shows that the diurnal variations of 

wind power output follow similar patterns from year to year, but that the magnitude of power 

production during a given month can vary significantly year to year. This point is emphasized in 

Figure 13 where large variations in the monthly energy output are evident when comparing the 

various years plotted. Summing the monthly energy production for these wind power plants near 

McCamey, Texas, U.S., to obtain an annual value, including summing their aggregate 

production, then plotting their annual energy output as a percentage of the 4-year average results 

in the plot shown in Figure 14. Comparing the year-to-year energy output from each wind power 

plant, the total energy produced varies by approximately ±10% of the average. Note the solid red 

line on this plot represents the output of all the wind power plants in aggregate, and the aggregate 

variability from year to year is generally less than for the any single plant in the area. 

0%

20%

40%

60%

80%

100%

120%

2004 2005 2006 2007

% of Annual Average Energy Prodcution

Year

Figure 14. Energy production as a percent of the annual average for several wind power plants 

near McCamey, Texas, U.S.; the solid red line represents the total energy production from 

aggregating all power plants together (cumulative nameplate capacity of ~690 MW) 

(Data source: NREL)
IEA Wind Task 24 Final Report, Vol. 1

30

2.3 Characteristics of Wind Power Ramping 

Another import aspect of wind plant variability in addition to the step changes in output from one 

period to the next is how rapidly the wind power may ramp from one output level to the next. 

The rate at which ramping may occur bears upon the amount of flexible generation a system 

operator must have access to for maintaining system reliability, which is especially critical 

within the hour of operation when the availability of flexible generation may be limited. Wan 

(2004) presents data on wind power ramp rates based upon 1-hour average power output data, 

defining a ramp rate as the magnitude of change during a time period of monotonic increase or 

decrease in wind power. Table 11 shows the magnitude of the average, minimum, and maximum 

ramp rates at the 103.5-MW wind power plant in Minnesota, U.S.. This data is also plotted with 

the ramp rate as a percent of maximum capacity per hour in Figure 15. Note most of the ramp 

rates, as defined here, are within ±20% of plant nameplate capacity.

Table 11. Statistical summary of ramp rates at a 103.5-MW wind power plant in Minnesota, U.S., 

based upon hourly power data (Source: Wan 2004)

Figure 15. Distribution of hourly ramping rate values (Source: Wan 2004)
IEA Wind Task 24 Final Report, Vol. 1

31

Figure 16 provides another method of defining ramp rates at a wind power plant that is more 

precise. The yellow line in this figure presents the 1-minute power output of a 63.7-MW wind 

power plant in Washington, U.S., and the blue line is a 15-minute rolling average of this data. 

The straight, red line segments are the effective ramps, which are defined as periods of 

monotonic increase or decrease in the 15-minute rolling average, neglecting sign changes of 

ramps with durations of less than 10 minutes. Ramps defined in this manner tend to represent the 

general trend in generation consistent with how load is followed within the hour and from hour 

to hour. Applying this method of defining ramps to 11 months of data from this wind power 

plant results in the sequence of ramp rates presented in Figure 17. The ordinate on this plot 

displays the ramp rate as a percent of nameplate capacity per minute, and the abscissa provides 

the number of ramps during the year. There were approximately 4200 positive and 4200 negative 

ramping periods, and most of the ramp rates were less than 1% of capacity per minute. In 

addition to the ramp rate, the duration of the ramp is also of importance as the long, steeper 

ramps are of greatest potential impact on system operation. For this same set of data, Figure 18

shows the number of ramps of a given duration tabulated versus the absolute value of the 

magnitude of the ramp. While the specific number of ramps in any particular bin (i.e., of a given 

duration and magnitude) is not necessarily of interest, the distribution of the ramps is of interest. 

At this particular power plant, there are very few short duration, high-magnitude ramps, and the 

preponderance of ramps are of a magnitude less than 30% of the nameplate capacity. Although 

there are few short-duration, high-magnitude ramps, these few ramps could cause difficulties and 

incur expense in system operation. The extent to which this occurs, however, depends on the 

change in the load net wind, the generation resources available, the accuracy of the wind 

forecast, etc.; in other words, it depends on the operation of the entire system inclusive of the 

wind power. Fortunately, as increasing amounts of wind energy are brought online, the overall 

magnitude of the ramp rates as a percent of total installed capacity tend to decline, due to the 

effects of geographic diversity and aggregation of wind power plant outputs, which is the topic 

of the next section.

Neglect 

changes 

of < 10 

minutes

Figure 16. A methodology for defining ramp rates at a wind power plant using a 15-minute rolling 

average of the 1-minute power output data, neglecting changes less than 10-minutes in duration 

when defining the end points of the each ramp
IEA Wind Task 24 Final Report, Vol. 1

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Figure 17. Positive (left plot) and negative (right plot) ramps rates expressed as a percentage of 

plant nameplate capacity at the 63.7-MW Nine Canyon Wind power plant in Washington, U.S., 

during 2006

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200 205

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160 165 170 175 180 185 190 195 200

0 5 0 1 1257 1852 898 667 514 418 310 250 164 137 107 95 66 63 34 34 39 32 17 11 19 18 16 11 15 11 12 8 8 12 9 2 5 5 6 5 3 4 6

5 10 0 0 11 133 162 161 166 151 112 125 92 80 67 48 45 32 34 19 17 15 10 13 8 9 9 3 6 3 4 4 4 4 3 2 2 0 0 4 2 0 0

10 15 0 0 1 17 42 45 41 49 58 38 48 36 34 39 28 25 10 19 14 10 4 12 8 10 8 2 5 5 4 2 4 3 0 2 3 1 0 0 1 1 0

15 20 0 0 0 5 5 27 27 24 22 19 20 19 28 19 19 15 17 14 15 10 11 4 5 1 8 11 1 3 4 2 3 3 1 2 3 1 1 1 0 0 0

20 25 0 0 0 1 6 6 12 9 7 16 16 17 13 14 10 13 12 6 6 8 6 5 4 7 2 4 4 0 2 0 0 0 0 1 0 0 0 0 2 1 1

25 30 0 0 0 0 2 0 5 5 5 11 10 7 3 4 4 8 7 9 4 5 2 3 1 3 7 3 3 3 1 3 0 0 0 3 1 0 0 2 0 1 0

30 35 0 0 0 1 0 2 3 1 5 7 2 4 1 3 3 2 3 1 6 1 3 4 3 3 5 2 4 2 4 0 2 0 0 1 0 0 0 0 2 0 0

35 40 0 0 0 0 0 1 1 2 1 2 0 2 1 5 3 2 2 3 1 1 4 3 1 2 0 1 2 2 5 2 1 1 1 2 1 1 1 2 0 0 0

40 45 0 0 0 0 0 0 1 0 1 0 1 2 1 0 2 2 0 1 2 3 1 1 0 1 1 2 1 1 0 2 1 3 3 0 0 0 0 0 0 0 1

45 50 0 0 0 0 0 1 1 2 0 1 1 2 0 1 1 2 1 0 3 0 2 0 1 0 1 1 0 1 1 2 0 0 0 0 0 0 0 0 0 0 0

50 55 0 0 0 0 0 2 0 1 0 1 4 0 1 0 3 0 0 2 0 0 1 2 2 2 1 0 0 2 1 0 2 0 0 0 0 0 0 0 0 0 0

55 60 0 0 0 0 1 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 2 1 1 0 0 0 1 1 0 0 0 1 0 0 0 0 0 1 1 0

60 65 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0

65 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

70 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

ramp durations

magnitudes

Very few short duration, 

high change ramps

Figure 18. Table demonstrating the distribution and duration of ramp events at the 63.7-MW Nine 

Canyon Wind power plant in Washington, U.S., during 2006 (magnitudes are in megawatts and 

durations are in minutes)

2.4 Impact of Geographic Diversity and Aggregation of Wind Power Plant Output 

on Wind Power Variations

Aggregating the output from numerous wind power plants tends to have a beneficial effect on the 

overall variability of the wind power being absorbed into a power system. This effect has been 

demonstrated via the results presented in Section 2.2, where the changes in output expressed as a 

percent of nameplate capacity per period (minute, hour, etc.) became smaller as the output was 

combined from multiple, spatially diverse wind power plants. That is, the variations that may 
IEA Wind Task 24 Final Report, Vol. 1

33

occur at a single wind power plant do not scale up linearly. The basic reason for this non-linear 

scaling effect is that the power outputs from spatially diverse power plants become less and less 

correlated as the spacing between them grows, and therefore more and more of the changes in 

power output at one power plant are to some extent countered by an opposite change in output at 

another power plant. This effect is evident at all spatial scales from groups of turbines within a 

single power plant that have a higher level of correlation to geographically distant wind power 

plants where the output may be completely uncorrelated. For example, consider the data shown 

in Table 12 (Wan 2005). The 14-, 61-, and 138-turbine groupings shown are from wind turbines 

at a single power plant, and the 250+ turbines represent the combined power output of two 

nearby power plants (including the 138 turbines). As demonstrated in this table, as more turbines 

are considered and the nameplate capacity of the turbines increases, the average magnitude and 

standard deviation of the step changes in wind power generally increase in magnitude, but 

generally decrease as a percentage of overall installed capacity. The magnitude of the numbers 

shown in this table will vary from site to site, but with consistent trends. Wan (2005) also shows 

that similar trends apply to the wind power ramp rates as for the step changes in power output.

Table 12. Step changes in wind power output from groupings of wind turbines located in 

Minnesota, U.S. (Source: Wan 2005)

The variability of the output in wind power plants is an important consideration in power system 

operation. Also of significance is the magnitude of the wind power output itself, and the 

relationship between the power output at geographically separated wind power plants. For 

example, how likely is it that numerous wind power plants be producing near their full output at 

the same time, or at no output? One might expect the output of wind power plants in the same 

general region, affected by the same weather patterns, to have a similar production pattern. 

However, as wind power plants become further separated, their output will be impacted by 

differing weather systems or topographical features, and one might expect their output to not be 

correlated. Wan (2005) considered the correlation coefficient between the power output at 

spatially separated wind power plants in the Midwestern U.S., resulting in the plot shown in 

Figure 19. There are four lines shown on this plot: one for the 1-second, 1-minute, 10-minute, 

and 1-hour average power production at the spatially separated power plants (note the 

logarithmic scale for the distance between the power plants on the abscissa). As shown, there is 

no correlation in the 1-second power output even for nearby power plants, and little correlation 

in the 1-minute power output. The correlation coefficients become larger for the 10-minute and 
IEA Wind Task 24 Final Report, Vol. 1

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1-hour time series for nearby power plants, diminishing to zero for geographically distant power 

plants.

Figure 19. Correlation coefficient between spatially separated wind power plants plotted as a 

function of the distance between them, for their 1-second, 1-minute, 10-minute, and 1-hour 

average power outputs (Source: Wan 2005)

2.5 Wind Power Forecasting and Uncertainty

As the previous sections of this chapter have demonstrated, there is a significant amount of 

variability associated with the generation from wind power plants. This variability occurs on all 

time frames of power system operation (seconds to years), with perhaps the most important

variations occurring in the 10-minute, 1-hour, and 1-day time frames. However, whether or not 

these variations cause significant impacts or incur appreciable costs depends upon many factors, 

such as the characteristics of the system load and generation, the penetration and characteristics 

of the wind power, the flexibility of the market, etc. As for the costs and implications on system 

reliability, one can imagine that if the wind power output and its variations can be well predicted, 

then the overall impact and cost of those variations can be minimized. To the extent that there are 

errors in the wind forecast that increase the uncertainty in the load net wind (i.e., the effective 

load signal that the system operator must balance with generation), additional reserves must be 

set aside to prepare for potential deviations between the forecast and actual load net wind. Thus, 

wind power forecasting is of significance in power system operation and modeling, and it is the 

purpose of this section to provide a brief overview of the state-of-the-art and implications on 

system operation.

There are three basic approaches by which wind power forecasts are created: physics-based 

numerical weather prediction (NWP) models, statistical models or combinations of the two

(Costa et al. 2008, Zack 2009). NWP models in use today include Mesoscale Model Version 5 

(MM5), the Weather Research and Forecasting Model (WRF), the High Resolution Limited Area 

Model (HIRLAM), etc. These models solve the complex equations of motion that govern 

atmospheric flows to produce predictions of weather variables such as the wind speed, direction, 

temperature, pressure, etc., which can then be converted to a prediction of the power output. The 
IEA Wind Task 24 Final Report, Vol. 1

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particular forecast approach one would use (NWP, statistical, or combination) depends upon the 

time frame of the forecast (i.e., the number of hours ahead of time for which the prediction is 

made). For very short-term forecasts, minutes ahead up to an hour, statistical methods that rely 

on recent wind speed and power production data dominate, for example using an auto regressive 

moving average model to predict future power output. From an hour ahead to several hours 

ahead, the forecast method might rely on an autoregressive prediction combined with an NWP

model and off-site data, and potentially use some type of genetic algorithm to improve forecasts 

based on previous performance. Beyond several hours ahead of time, the state-of-the-art is 

represented by NWP models that are statistically corrected to better match the actual power 

production at a given site (e.g., using model output statistics). The performance of a single, 

deterministic prediction based on an NWP can be improved upon by ensemble averaging. In this 

type of averaging, the input conditions and assumptions are modified in some fashion within 

their range of uncertainty, and the NWP model is re-run. After performing multiple runs, the 

outputs of the NWP are then averaged or otherwise combined, typically resulting in a better 

performing forecast. Ensemble averages can also be produced when using purely statistical 

techniques, or by combining both statistical and NWP methods. 

Wind power forecast models can be set-up to provide a “deterministic” forecast, such as a single 

most-likely value, or a “probabilistic” forecast that predicts not only a most-likely value but also 

confidence interval. For example, see Figure 20 from Ernst et al. (2007). The basic idea with a 

probabilistic forecast is to provide more information to the system operator from which to make 

decisions. At present, addressing the issue of how to best integrate wind forecasting into system 

planning and operation is a work in progress, and wind forecast providers are working with 

system operators and others to devise useful methods to bring wind power forecasts into system 

planning and the control room.

Figure 20. Plot of a wind power forecast from WEPROG’s MSEPS system (see www.weprog.com/) 

including uncertainty bands (black and gray shading); a few methods of predicting the expected 

output (orange dashed, white, and yellow lines); and the predicted maximum and minimum 

possible values (top red and bottom green lines)—the actual output is shown by the bold, black, 

dashed line (Source: Ernst et al. 2007)
IEA Wind Task 24 Final Report, Vol. 1

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Any power system that incorporates significant amounts of wind power probably either uses a

professional wind forecast based upon an NWP model, or is interested in doing so. General 

Electric, in its study of integrating wind power into the New York independent systems 

operations, showed that the value of a state-of-the-art “professional” wind forecast improved the 

value of wind energy by about 25% (Piwko 2005), or $10.70/MWh of wind energy produced, 

relative to using no forecast at all. This value was attained by including the wind forecast in the 

day-ahead commitment process of the cost production simulation, in effect reducing the planning 

uncertainty and permitting more economical use of the existing system resources to meet the 

load net wind. Barthelmie et al. (2008) presents a study of short-term wind forecasting in the 

United Kingdom electricity market, and similarly shows an economic benefit to wind power 

forecasting.

As for the performance metrics that describe the accuracy of a professional forecast, the mean 

absolute error (MAE) or the root mean square error (RMSE) are the most frequently cited. The

MAE is computed by determining the forecast error for the forecasted hours hour being 

considered (e.g., typically one year or more), taking the absolute value of these errors, and then 

calculating the mean. The RMSE is slightly different; it is calculated by finding the difference 

between the forecasted and actual wind power generation for each hour of the time period under 

consideration, squaring this difference, summing these squared values, and computing the 

average, then taking the square root of this average. Because the difference is squared in this 

calculation, large errors in the forecast are weighed more heavily, and the RMSE is greater than 

the MAE. For a typical professional forecast, both the MAE and RMSE are relatively low for 

short-term forecasts, reflecting overall accuracy in the mean. For example, the plots in Figure 21

show the MAE (plot on the left) and the RMSE (plot on right side) for a relatively small 

(~ 60-MW) wind power plant in the United States. Both of these plots show the error plotted 

versus time horizon of the forecast, varying from 1 hour ahead to 50 hours ahead. There are three 

forecast methods plotted: climatological (in this case, forecasting the output to be the annual 

average); persistence (the forecast for any future hour is equal to the wind power production 

during the last hour); and professional (based on an NWP and/or statistical models and field 

data). The professional forecast shown represents a state-of-the-art forecast in the period from 

2004–2006; three years of data were used to create these plots.
IEA Wind Task 24 Final Report, Vol. 1

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Figure 21. Plots of the mean absolute error (MAE) and root mean square error (RMSE) versus 

number of hours of lead time for the forecast, for a wind power plant in the USA; the errors for 

three types of forecasts are displayed: professional, persistence, and climatological

(Source: Northern Arizona University)

The “elbow” shown at the eighth hour in both plots for the professional forecast occurs because 

of a change in forecast methodology employed. In essence, what happens at this point is that 

NWP based models begin outperforming statistical models for the longer term forecasts, and the 

change in methodology results in the elbow observed in the plots. A good description of this 

phenomenon can be found in the paper by Costa et al. (2006). As one can see, the hour ahead 

error for the professional forecast is about 6% (MAE) or 10% (RMSE), increasing to about 17% 

(MAE) and 26% (RMSE) at 24-hours ahead. In every hour, the professional forecast beats the 

performance of the persistence and climatological forecasts, and rather substantially for forecasts 

beyond eight hours. This increase in certainty of generation leads to cost savings in system F

Figure 21. Plots of the MAE and RMSE versus the number of hours of lead time for the forecast, 

for a wind power plant in the United States; the errors for three types of forecasts are displayed: 

professional, persistence, and climatological (Source: Northern Arizona University)

System operators and planners are concerned with being able to securely operate the system

during all hours of the year, and are therefore keenly interested in the “outlier” events where the 

wind forecast may be greatly in error and the ability to maintain system reliability may be tested. 

Figure 22 shows a graph of the hour-ahead MAE for the same professional wind forecast as 

displayed in the previous figure, but sorted by the hourly change in wind power production. Note

the overall MAE for the hour-ahead wind forecast denoted by the red “+” matches the hourahead forecast error from Figure 21. As one considers increasing magnitudes of hourly changes 

in wind output, the MAE of forecast error during these hours becomes increasingly large. 

However, as the black line indicates, there are relatively few hours during the year when these 

large hourly changes occur. A few observations can be made from this figure: (1) the forecast 

errors at the various levels of hourly change are roughly symmetric about zero; (2) when there 

are small hourly changes in wind power output, which is most hours of the year, the MAE is 

quite low; and (3) when significant changes in power output occur, the system operator and 

planner need to plan additional reserves due to uncertainty in the output, whereas when there are 

small changes in output forecasted, there is more certainty in the forecast and less reserve need 

be set aside. Note, for larger wind power plants, or where several wind power plants are 

aggregated in a balancing area, the overall magnitude of the MAE in each bin will likely reduce. 

Figure 23 presents another way of displaying this information. Here, the plot is made with the 

same data but using the absolute value of the hourly change on the abscissa. It is perhaps more 

obvious on this chart the difficulty in forecasting wind power during large ramping events, and 

that these events occur very infrequently. Note for very large hourly changes in generation that 

the MAE is quite large. One current area of research in wind forecasting is improving forecast 

performance (reducing the MAE or RMSE) for hours where the generation changes are large, 

essentially predicting the large wind power ramping events better. Concerning the system 
IEA Wind Task 24 Final Report, Vol. 1

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operator, understanding when to look out for large ramp events (and when not to) is key to 

minimizing the cost associated with wind forecast errors.

Figure 22. Plot of the hour-ahead mean absolute error, sorted by the hourly change in output of 

the wind power plant; the blue, dashed line corresponds to the mean absolute error, the black line 

denotes the frequency of occurrences in each bin of hourly changes, and the red cross identifies 

the overall mean absolute error (for all hours, regardless of hourly change) (Source: Northern 

Arizona University)

Figure 23. A plot demonstrating the hour-ahead MAE and cumulative frequency count as a 

function of the hourly change in wind power plant output (Source: Northern Arizona University)

As was mentioned with respect to the variability of the wind power in the previous sections, it is 

the overall variability of the load net wind that is of importance to the system operator and 

planner, and not the variability of the wind power by itself. The same is true for the forecast 

error. Just as the system planner and operator must address the variability of the load net wind, 

so too must they plan for the combined forecast error of the load and the wind power. Thus, the 

overall impact of forecast error and variability must therefore be addressed in the context of the 

entire system, its resources, characteristics, and loads.

2.6 Capacity Value of Wind Resources

As mentioned previously in Section 2.1, the capacity value of a wind power resource is related to 

its power production during the peak hours of the year. To the extent that wind power is 

available during the peak hours, it can displace the need to build other capacity resources on the 

system and thus has a capacity value. No single method is agreed on for computing a capacity 
IEA Wind Task 24 Final Report, Vol. 1

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value of wind resources; however, a common method to determine the capacity value of a wind 

power resource is to compute the ELCC, which is defined as the amount of additional load that

can be served at a prescribed reliability level with the addition of a given amount of generation. 

This ELCC is based on one of several reliability metrics, such as the loss of load probability or 

the loss of load expectation. Determining the ELCC can be accomplished using a power system 

reliability model, and is fairly data intensive. Milligan has suggested an alternative, approximate 

method to determine the capacity value of wind power (Milligan and Porter 2007, Milligan and 

Parsons 1997). While this method is not a substitute for utility techniques of computing the 

ELCC of a generator (or some other similarly rigorous technique), it has been shown to provide a 

fair indication of the wind’s capacity value, within a few percent. The basic idea of this 

technique is to compute the average capacity factor during the highest 10% of load hours during 

the year. Taking this value of the capacity factor and multiplying by the nameplate capacity then 

provides an approximation of the capacity value from the wind power plant. Two points of 

interest generally emerge from application of this method: (1) the capacity value will normally 

be less than the average capacity factor for the entire year; and (2) the wind power will have a 

capacity value that is a significant fraction of its average capacity. The capacity value of wind 

has been shown to range from approximately 10% to 40% of the wind-plant rated capacity 

(Smith et al. 2007). Some of the data shown were computed using the ELCC method, and others 

used simplified methods, such as suggested by Milligan.

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

NYSERDA

Onshore

NYSERDA

Offshore

MN/Xcel(1) CO Green MN/Xcel(2) MN 2006 PacifiCorp CA/CEC

ELCC as % Rated Capacity

Figure 24. The capacity value of wind power as determined in several wind integration studies in 

the United States (Source: Smith et al. 2007)

2.7 Environmental Attributes

Wind energy, like every generation resource, has environmental impacts. On the positive side, 

wind energy does not produce any pollutant air emissions and requires no water, the latter of 

which is of importance in arid regions of the world. Indeed, one of the positive benefits of using

wind power is that to the extent it displaces thermal power generation, it avoids emissions and 

water use. The negative impacts of wind energy include noise, visual impacts, and avian and bat 

mortality. With respect to noise, modern wind turbines that have relatively slow rotation rates 

(<20 revolutions per minute) tend to be fairly quite. However, depending on the proximity to 
IEA Wind Task 24 Final Report, Vol. 1

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people or wildlife, noise may still be an issue. These visual and noise impacts, as perceived by 

any given community, can often be minimized through proper siting and must be considered 

during the public permitting process that accompanies siting of a new wind power plant. Perhaps 

the most significant environmental impact is that due to avian and bat mortality. Design 

improvements over the past several years, such as using monopoles (no lattice towers) and 

reducing the blade rotation rate, have significantly reduced the impact on mortality. Furthermore, 

appropriate siting can help avoid poor locations where some bird species may be at risk, such as 

migratory flyways. Bat mortality has recently become a problem at some North American wind 

power plants, and is an active area of research and concern (Kunz 2007, NWCC 2004).

2.8 Summary of Wind Variability and Uncertainty: Considerations in System 

Planning and Operation

In this chapter, several important aspects to wind power were presented. When considering wind 

power, there are several contributing factors to its overall value in the power system. The 

collective impacts of these factors typically lead to a net positive economic value, 

acknowledging that there may be instances when this is not the case, dependent upon the specific 

utility or electrical system and its market. One of the cost components of wind energy is the 

“integration” cost, due to the effects of wind power’s variability and uncertainty on system 

operation. NREL (Wan 2004, 2005, 2008) has published some insightful reports describing the 

variability of wind power, based on the output of actual wind power plants in the United States. 

The data presented in this chapter was intended to provide a sense for the order of magnitude and 

frequency of power output changes with which a system operator or planner must contend. The 

data suggest that there will be a relatively small impact at the regulation (minute to minute) time 

scale, but becoming considerable at the hourly time scale and beyond (e.g., load following, unit 

commitment, reserve requirements). In addition to being variable, wind power is also uncertain, 

and though accurately predictable much of the time, can suffer from large forecast errors that 

may occur at inopportune times during system operation. Wind power, while primarily an energy 

resource, does have a capacity value that should be considered in system planning. Another 

positive aspect of wind energy is its environmental attribute of being a carbon-free, water-free 

energy generation technology. What makes wind power different to a system operator and 

planner as compared to other power resources is its variability and uncertainty, and learning how 

to understand and work with these characteristics. The overall impact of the wind power 

variations, forecast errors, and their associated integration cost, combined with the cost of wind 

energy, its marginal value, and the positive benefits it brings to the electrical system, depend on a 

host of factors, including the system load, the generation fleet, operational and market flexibility, 

etc., and can only be accurately estimated via a thorough cost production simulation of the power 

system. The methods employed in carrying out such a simulation are presented in Volume 2, 

Chapter 1, of the Task 24 report. Results of such studies pertaining to wind and hydropower 

integration will be discussed in Chapter 4. 
IEA Wind Task 24 Final Report, Vol. 1

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3 Hydropower System Planning and Operation

3.1 Introduction

Hydropower was one of the original and principal sources of electrical energy in the early and 

mid-20th century. Since then, the world’s electricity production has become predominantly fossil 

fuel based, and with energy demand continuing to escalate, pressures on the world’s climate and 

general environmental well-being are also growing. In most countries, hydropower’s role is a 

smaller percentage (in terms of overall energy production) than in the past, although it is often 

important for the provision of ancillary services, including storage. One reason hydropower is 

used less often now than in the past is that it takes less time to design, approve, build, and 

recover investment from thermal power plants, which are also less constrained in their operation. 

However, thermal power plants have higher operating costs; typically shorter operating lives 

(about 25 years); are sources of air, water, and soil pollution and greenhouse gases; and provide 

fewer opportunities for economic spin-offs. In assessing life cycle costs, hydropower 

consistently compares favorably with virtually all other forms of energy generation, and is 

therefore a preferred power resource.

Over the last two decades, the development of new hydropower projects as well as the 

modernization of existing plants, while still significant, has been under increasing pressure for a 

variety of financial, environmental, social, and regulatory reasons. However, hydropower’s role 

in integrating other renewable energy sources, especially wind energy, has the potential to grow 

both in extent and importance. While fluctuating power levels and transmission constraints have 

hampered ready adoption of wind energy to the utility grids worldwide, fluctuating water levels, 

growing pressures on water supplies, the need for flood controls, and environmental issues are 

just a few of the constraints that may limit future growth of hydroelectric production. 

Hydropower provides unique benefits rarely found in other sources of energy. These benefits can 

be attributed to the electricity itself or to side-benefits, often associated with reservoir 

development. 

Despite the recent debates, few would disclaim that the net environmental benefits of 

hydropower are far superior to fossil-based generation. While development of all the remaining 

hydroelectric potential could not hope to cover total future world demand for electricity, 

implementation of even half of this potential could have enormous environmental benefits in 

terms of avoided generation by fossil fuels, especially if deployed in a manner in which the 

hydro flexibility can support the additional ancillary services requirements brought about by 

wind power or other variable renewable energy resources.

Generally speaking, several attributes of hydropower are as follows:

1. Hydropower resources are widely spread around the world. The potential use of 

hydropower exists in approximately 150 countries, and about 70% of economically 

feasible areas remain to be developed, which is primarily in developing countries. 

2. Hydropower is a proven and well-advanced technology with more than a century of 

experience, and modern hydropower plants are capable of very efficient energy 

conversion (>90%).
IEA Wind Task 24 Final Report, Vol. 1

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3. Hydropower plays a major role in reducing greenhouse gas emissions in terms of avoided 

generation by fossil fuels. Hydropower is a relatively minor source of atmospheric 

emissions compared with fossil-fired generating options.

4. The production of peak load energy from hydropower complements the base load power 

from other, less flexible electricity sources. Hydropower’s fast response time enables it to 

meet sudden fluctuations in demand. 

5. Hydropower has the lowest operating costs and longest plant life compared to other 

large-scale generating options. Once the initial investment has been made in the 

necessary civil works, plant life can be extended economically by relatively inexpensive 

maintenance and the periodic replacement of electromechanical equipment (e.g., 

replacement of turbine runners, rewinding of generators) and, in some cases the addition 

of new generating units. A hydro plant in service for 40–50 years can typically have its 

operating life doubled. 

6. Hydro plants are very often integrated within multipurpose developments, which are

satisfying other fundamental human needs (e.g., irrigation for food supply, domestic and 

industrial water supply, flood protection). Reservoir water may also be used for other 

functions such as fisheries, discharge regulation downstream for navigation 

improvements, and recreation. 

7. Hydro plants’ “fuel” (water) is renewable, and is not subject to fluctuations in market 

conditions. Hydropower can also represent energy independence for many countries. 

8. Positive engineering attributes of hydropower include integrated controllability and 

response time of generators, transmission systems linking the physical locations of the 

hydropower with the system load, and the characteristics of the utility electric load. 

9. The capacity of the reservoirs and the seasonal and yearly inflow variability for dry, 

normal, and wet years is an important consideration in long-term planning of hydro 

generation.

10. In comparison with hydropower, thermal plants take less time to design, obtain approval

for, build, and pay back. However, they have higher operating costs; typically shorter 

operating lives (~25 years); are key sources of air, water, soil pollution, and greenhouse 

gases; and provide fewer opportunities for economic spin-offs.

The purpose of this chapter is to describe the aspects of hydropower relevant to wind and 

hydropower integration, establishing what is unique about hydropower relative to other flexible 

power resources used for system balancing or energy storage, and helping set the context for the 

results to be described later in this report.

3.2 Types of Hydropower and Energy Storage

Many renewable energy technologies are variable in nature, meaning they are not continuously 

available, because they rely on the wind or sun. All hydroelectric generating plants, except for 

the very smallest can, to a greater or lesser extent, store water and therefore energy, and then 

release it to generate electricity when required. This ability to store energy is an asset that can be 

combined with other renewable technologies like wind energy to enable larger-scale use of 

renewable energy. Hydropower owners can also use this as a source of revenue.
IEA Wind Task 24 Final Report, Vol. 1

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3.2.1 Hydro Storage

The fundamental principle of a hydropower plant is to construct a barrier (dam, dyke, or barrage) 

across the flow of a river, store the water behind this barrier, and generate electricity through 

hydraulic turbines when there is a demand for the energy (see Figure 25). If more water flows 

down the river than can be used for generation, the excess water flows over the spillway across 

the top of the dam or through sluices of various types. Therefore, the design of many hydroelectric developments has, in the past, been based on optimizing generation (and spill avoidance) 

versus storage, with the result that many projects with high dams and very large storages have 

been developed. This objective is concomitant with flood control. These large storage projects

can have the greatest potential for significant system integration with wind power in terms of 

storage (shifting water and energy releases for days to months) and ancillary services. For 

example, if excess wind generation is available, it may be possible to reduce the flow through a 

hydropower facility and save it for a later time. Hydro projects with small reservoirs may also 

possess decent potential for integration with wind, though mainly in providing ancillary services 

related to the shorter time scales (regulation, load following, reserves), but also via energy 

storage from hours to a couple days. In mountainous areas, with high precipitation (snow fall 

and/or rain), many large hydro plants have small storages and modest flows, but high hydrostatic 

heads12. These hydro plants often use slow snowmelt as their primary storage mechanism, and 

similarly, may be capable of providing ancillary services on shorter time scales. 

Figure 25. (a) Typical configuration of a dam and hydropower plant; (b) a pumped-hydropower 

plant (Source: Tennessee Valley Authority, www.tva.gov/power/hydro.htm)

The typical setup of water impoundment behind a dam with hydro turbines is not the only 

possible water storage configuration. In some cases, storage is sometimes augmented by large, 

on- or off-stream storages, using barriers placed across rivers or lakes to provide additional 

storage without hydropower generation at the site. The flows can be released as required, and 

connected to the hydro developments by tunnel or canal, or along the original waterway. 

3.2.2 Run-of-the-River Hydro

Run-of-the-river hydropower plants are constructed with the aim of using hydropower for 

generation of electrical energy without the construction of large water impoundment reservoirs. 

A “pure” run-of-the-river hydro plant would have no storage at all and simply use water as it 

comes down the river. However, in most cases, some level of storage is associated with a run-of-

 12 The term head often refers to the height of the reservoir surface above the generators. The higher the head is, the 

greater potential for power generation (power = head height × flow rate of river × efficiency of generators).
IEA Wind Task 24 Final Report, Vol. 1

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the-river dam, varying from several hours to 2 weeks of flow in the river. Often, when run-ofthe-river hydro is employed on a river, there will be several dams and power plants leading to the 

building of reservoir cascades along rivers (i.e., several run-of-the-river hydropower plants in 

succession on a single river). The illustration of a hydropower facility shown in Figure 25 is 

most like a run-of-the-river hydro plant, with a relatively low height of the dam.

3.2.3 Pumped Storage

Pumped hydro-electricity storage is one of the oldest and largest of all the commercially 

available energy storage technologies. It is a method of storing and producing electricity to meet 

high-peak demands, working on a simple principle. As shown in Figure 25, two reservoirs at 

different elevations are required. When the water is released from the upper reservoir, the

downward flow is directed through high-pressure shafts, linked to turbines, which in turn power 

the generators to produce electricity. In storage mode, water is pumped to the upper reservoir by 

reversing the generators and running them as motors. About 70% to 80% of the electrical energy 

used to pump the water into the elevated reservoir can be recovered in this process. A typical 

mode of operation for such a plant is to pump the water during off-peak hours when electricity is 

inexpensive, and then release the water during on-peak hours when the value of the electricity is 

very high (a process referred to as load factoring). Assuming an 80% “round trip” efficiency, the 

minimum price differential between the off-peak and on-peak electricity must be (1÷ 0.8)= 1.25 

in order for the pumped hydro to be affordable; in other words, the cost of running a pumped 

hydro facility cannot break even unless the on-peak price is at least 25% higher than off-peak. If 

the roundtrip efficiency is 70%, then this percentage increases to 43%. Even with this 

requirement, as a system resource (i.e., a resource that is valuable in balancing the overall 

variations of load in a balancing area), pumped hydro can be a cost-effective peaking resource. 

With respect to providing the enhanced ancillary services as required by wind integration, 

pumped hydro is a viable option only if its ability to provide ancillary services is more valuable 

than the load factoring it currently provides. One wind integration study conducted in the United 

States for a utility in Colorado considered the value of a large (>300 MW) pumped storage 

facility in reducing wind integration costs (Zavadil 2006). At a 10% penetration of wind energy 

(wind capacity divided by peak load), the benefit of pumped hydro was small, and suggested that 

new investment in pumped hydro for the benefit of wind integration would not be cost effective. 

As such, the prevailing opinion is that pumped hydro, due to its large capital costs, will not likely 

be cost effective for wind integration until wind penetration levels get quite large (30% to 50%). 

For this reason, storage in this study focuses on conventional hydro, in which no efficiency 

penalty is incurred as it is for pumped hydro, and the storage is accessed by altering flow 

schedules through the generators and retaining water in the reservoirs. 

3.2.4 Other Non-Hydropower Storage

3.2.4.1 Flow Batteries

Flow batteries, or regenerative fuel cells, can store and release energy through a reversible

electrochemical reaction between two salt solutions (electrolytes). These systems are good for 

storage of real power (megawatts), but poor for quick delivery of reactive power (mega volt 

ampere reactive). Various electrolytes have been used, including zinc bromide, vanadium 

bromide, and sodium bromide. The battery is charged as electrical energy from the grid is 

converted into potential chemical energy. Within the electro-chemical cell, there is a separate 
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compartment for each electrolyte, physically separated by an ion-exchange membrane to allow 

release of the potential energy to occur. The cycle is a closed loop, so there is no discharge, and 

the size of the storage is limited by the size of the electrolytic tanks. 

3.2.4.2 Batteries

There are a number of battery technologies for storage use on a utility-scale. Lead acid is the 

dominant battery type, although other batteries—such as sodium sulphur and lithium-ion—are 

also available. Batteries are electrochemical cells composed of two electrodes separated by an 

electrolyte. When a battery is discharging, ions from the first electrode (anode) are released into 

the solution, and oxides are deposited on the second electrode (cathode). To recharge the battery, 

the electrical charge is reversed, returning the battery to its original condition.

3.2.4.3 Superconducting Magnetic Energy Storage

Superconducting Magnetic Energy Storage systems store energy in the magnetic field created by

direct current flowing in a coil of cryogenically cooled superconducting material. Such a system 

requires a superconducting coil, a cryogenically cooled refrigerator, and a vacuum vessel. It is 

claimed that these systems are 97–98% efficient and can provide both real and reactive power. 

Superconducting Magnetic Energy Storage systems can store energy with a loss of only 0.1% per

hour, compared to a loss of approximately 1% per hour loss for flywheels. They can recharge in 

minutes and can repeat the charge/discharge sequence thousands of times without any 

degradation in the magnet, with recharge time being tailored to meet specific requirements 

depending on system capacity. Such storage facilities are used to provide grid stability in a 

distribution system and for maintaining power quality at advanced manufacturing plants. 

3.2.4.4 Flywheels

Flywheels store energy by accelerating a rotor to a very high speed and storing this energy in the 

system as inertia. The rotor must be low weight and allow for the extremely high speeds, so it is 

manufactured from advanced composite materials. The energy is released from the flywheel by 

reversing the process to use the motor as a generator, so that the rotor gradually slows down until 

it is discharged. These flywheels only produce 5–10 kW of power. Size is a consideration

because flywheels are often relatively large, and currently do not have very large storage 

potential. 

3.2.4.5 Compressed Air Energy Storage

Compressed Air Energy Storage is a method of storing energy in large quantities of compressed 

air that is later run through a turbine to generate electricity. Off-peak or low-cost electricity is 

used to drive a compressor that will force air into an underground storage cavern. When electric 

power demand peaks during the day, the air is then released from the cavern and run through 

combustion turbine. The turbine, which requires compressed air to operate, then creates 

electricity through connection with an electrical generator. For example, a salt cavern can be 

used to store the compressed air at high pressures (7,600 kilo pascal [kPa]/1100 psi), with a 

magnitude of up to a day’s worth of production depending on plant and cavern size, with a 

storage efficiency of up to 85% (i.e., on the order of 15% of the energy used in compression is 

not recovered). Turbines that run off the compressed air vary in size and can exceed 100 MW.
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3.2.4.6 Hydrogen

There are concepts in development for the conversion of energy from remote renewables to 

hydrogen gas via electrolysis of water. This process is about 65% efficient. The hydrogen gas

could then be stored before powering fuel cells connected to the remote system. However, the 

efficiency of this process is a concern, and this technology is still under development.

3.2.5 Summary of Storage Options

Table 13 summarizes the relative cost, size, efficiency, and maturity of the various energy 

storage options. All of these options are possibilities for assisting in addressing the enhanced 

ancillary service requirements caused by wind energy, but only the least expensive options will 

generally be employed. Nickell (2008) suggested that the relative cost and flexibility of the 

various flexible generation resources, storage, or market mechanisms could be represented as 

shown in Figure 26. While this figure only shows a qualitative trend, it appropriately suggests 

that studying the potential of energy storage in conventional hydropower (versus pumped 

hydropower or other storage technologies) is a good place to start.

Table 13. Approximate capital costs, efficiency, capacity, and level of maturity of various 

alternative energy storage technologies

Pumped 

Storage

Compressed 

Air

Superconducting 

Magnetic

Flywheels 

(highspeed)Hydrogen

Capital Cost 

($/MWh) 7,000 2,000 10,000 25,000,000 15,000

Efficiency 0.8 0.85 0.97 0.93 0.45–0.8

Capacity 22,000 MWh 2,400 MWh 0.8 kWh 750 kWh 0.3 to 2,000 kWh

Maturity Mature 

commercial Commercial Commercial New Commercial

Commercial 

Developing
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Figure 26. A “Flexibility Supply Curve” that qualitatively compares the various options for 

provision of ancillary services (Source: Nickell 2008)

3.3 River Systems

One of the characteristics that distinguish hydropower from other generation resources is the 

widely varying flexibility of the generation units at different hydropower plants, dependent upon 

the uniqueness of each plant, such as its dam height and reservoir size, river flows, 

environmental factors, and other priorities. The relationship that exists between hydropower 

facilities located on the same river system also distinguishes hydropower from other generation 

resources. The purpose of this section is to describe some of the complexity that exists in this 

latter relationship, and, in particular, as it pertains to hydro system flexibility and 

wind/hydropower integration.

Each hydropower plant has distinctive characteristics because the plants are designed on a large 

group of inputs, sometimes conflicting, that include hydrology, geology, topography, 

socio/environmental impacts, system constraints, and power demand requirements, all optimized 

against highest value. In any river system, there can be the choice of developing a few large 

projects or a larger number of smaller projects. It is usually considered that the optimum system 

development is to have large storages in the up-stream projects, followed by lower head, but 

higher flow projects, downstream. This allows more flexible operation of the individual river 

system, by releasing flows, as required, from the upper storage reservoirs and generating on a 

run-of-river basis downstream. The flow travel time, and hence distribution with time of energy 

generation across hydro plants in the system, can be readily modeled and included in system 

operating rules. In many system-operating models, it is possible to consider the river system as a 

single, very flexible, generating unit.

In most cases—due to the large capital investment required, the use of public lands, and the long 

payback period—hydropower plants are typically financed and built by large public utilities or 

by governments, but not normally by private companies. Depending on the country and its 
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approach through which hydropower has been developed, there is a wide range of possible 

combinations of hydropower plants. For example, the hydro plants on a given river system may 

have been built with an overall plan in mind (with respect to power generation) by a single 

agency—or, one dam at a time, by different organizations with different priorities. In the former 

case, with one organization owning and operating the dams on a river system, it is very likely 

that the overall operation of the hydro plants is optimized as suggested above: as one very 

flexible generating unit. In such an arrangement, given a certain level of required generation, the 

units can be operated to maximize the power output (per unit of water flow) for the entire system 

over the course of a day (typically, but possibly some other period of time). Alternatively, for 

river systems in which there are multiple hydropower owners and operators, if one hydro plant is 

run to the maximum benefit of its owner without consideration of others, the downstream power 

plants will likely not be able to run in an optimal sense. For example, some reservoirs may 

become depleted and forced to operate with lower heads, while others become overfilled, 

increasing the possibility of spilling water without generating power. Furthermore, depending 

upon when water is released from the upstream dams, the arrival of stream flows at downstream 

reservoirs may not be during the peak electricity consumption hours of the day, which could be a 

problem for run-of-the-river hydropower plants with little storage.

To demonstrate the type and variety of hydropower systems within representative river systems, 

two example systems are described in the following sections.

3.3.1 Example River System with Multiple Owner/Operators: the Columbia River 

in the United States and Canada

An example of a complex interaction of hydropower plants along a single river system can be 

found along the Columbia River system, which runs through southwestern Canada and the 

Northwestern United States. As shown in Figure 27, there are in excess of 40 hydropower plants 

in the river system, with multiple owners/operators, split across two countries and four states. 

With many hydroelectric facilities located along the river, hydro operators realized early on that 

there were important benefits to coordinating their operation. In 1964, this cooperation was 

formalized in the form of the Pacific Northwest Coordination Agreement. A main goal of this

agreement was to try to optimize benefits of the hydro facilities all along the river by emulating 

the coordinated operation that could be achieved if operated by a single owner. Priorities of this 

agreement include producing firm energy based on very low historical stream flows, refilling 

reservoirs, and producing surplus energy with higher stream flows. Each of these priorities, 

however, is subservient to meeting Non-Power Constraints, such as those within the Vernita Bar 

Agreement.13

 13 For more information about this agreement, see 

This agreement sets flow requirements from the Priest Rapids dam needed for the 

spawning of fall Chinook salmon in the Columbia River. 

http://www.nwcouncil.org/library/isab/isab98-5.htm. 
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Figure 27. Map of dams in the Columbia River Basin (Source: U.S. Army Corps of Engineers, 

www.nwd.usace.army.mil/ps/colbsnmap.htm)

At the head of the mid-Columbia system, the U.S. Bureau of Reclamation operates the Grand 

Coulee dam and power plant. It is a large storage project (approximately 9,500,000 acre-feet or 

11,700 cubic hectometers) with 6,809 MW of nameplate generating capacity. The electricity 

generated at Grand Coulee is scheduled and marketed by the Bonneville Power Administration, 

and represents one of its most flexible resources. As indicated in Figure 27, this dam is located 

upstream of six essentially run-of-the-river dams on the mid-Columbia, whose names, 

owners/operators, and the nameplate capacities are as follows: 

(a) Chief Joseph: U.S. Army Corps of Engineers (USACE), 2,069-MW nameplate 

(b) Wells: Douglas County Public Utility District (PUD), 840-MW nameplate 

(c) Rocky Reach: Chelan County PUD, 1,287-MW peak 

(d) Rock Island: Chelan County PUD, 660-MW peak

(e) Wanapum: Grant County PUD, rated at 1,038 MW 

(f) Priest Rapids: Grant County PUD, rated at 955.6 MW

The operation of Grand Coulee significantly influences the operations at these six dams because

its flow takes approximately 9.5 hours to travel from Grand Coulee to Priest Rapids (although 

time varies depending on flow rate). The flow out of Priest Rapids is highly regulated as it flows 

into an environmentally important region of the Columbia, as prescribed by the Vernita Bar 

Agreement. For example, Figure 28 shows the discharges from Grand Coulee and Priest Rapids 

dams during a week in March 2001. The flow output from Grand Coulee is highly variable, 

whereas the flow output from Priest Rapids is not. During this particular week, there was a nonpower flow constraint from Priest Rapids for the protection of incubating salmon.

MidColumbia 
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Figure 28. Plot showing the discharge of water from Grand Coulee dam and from Priest Rapids 

dam during a week in March 2001 (Source: Acker et al. 2006)

Due to the challenges in optimally planning hydro generation amidst multiple constraints and 

uncertainties, especially in the hourly-to-weekly time frame, the owners of the seven projects on 

the mid-Columbia from Grand Coulee to Priest Rapids have entered into the Mid-Columbia 

Hourly Coordination Agreement. The prime objectives of this agreement are to keep the six 

reservoirs downstream of Grand Coulee full, minimize radical fluctuations in forebay levels, and 

prevent or minimize unintended spilled water by facilities on the river, therefore focusing on the 

maximization of power output from the projects. This coordination has been implemented by 

forming a “Central” dispatch to which the generation requests of each of these projects are 

submitted. Central receives “uncoordinated” requests every four seconds, then re-dispatches 

coordinated requests to the Federal Projects at 20-minute intervals, and to the non-Federal 

projects at 4-second intervals, in an effort to optimize the output of the entire system. In 

implementing this coordination, all the rights and obligations of each project participant are 

preserved. Additionally, detailed accounting is conducted, and periodic adjustments made, to 

ensure that each participant receives its appropriate share of the generating capacity, inflow, and 

pondage.

As demonstrated through this example of the mid-Columbia dams, there can be a significant 

amount of complexity and organization required for optimally running the hydropower along a 

river system. Numerous organizations, agreements, and regulations may be required, resulting in 

improved overall efficiency or energy production, but may either increase or decrease the 

flexibility, and create rigid operating agreements that are difficult to modify. 

Grand Coulee and Priest Rapids Total Discharge

Minimum Protection Flow of 70 kcfs at Priest Rapids

-

20

40

60

80

100

120

140

160

180

03-24-2001

Sat

03-25-2001

Sun

03-26-2001

Mon

03-27-2001

Tues

03-28-2001

Wed

03-29-2001

Thur

03-30-2001

Fri

Discharge in kcfs

Grand Coulee Discharge Priest Rapids Discharge

River is reregulated at Priest Rapids

Other Mid C projects are also affected
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3.3.2 Example River System with a Single Owner/Operator: the Missouri River in 

the United States

As compared to the Columbia River, a distinctly different river system in the United States is the 

Missouri River. Along the main stem of this river are six large dams at locations displayed in

Figure 29. The hydropower plants located at these dams possess a total generating capacity just 

below 2,400 MW. All facilities are owned and operated by the U.S. Army Corps of Engineers. 

The combined water storage capacity in these reservoirs is three times the annual runoff, so there

is some flexibility in timing of water releases. Operation of these large dams and hydropower 

facilities has a dominating effect over the water operations in the entire region. In order to 

achieve the multi-purpose benefits for which they were created, the six reservoirs are operated as 

a hydraulically and electrically integrated system. This coordination is accomplished via a 

Master Manual published by USACE. The Master Manual serves as a guide in meeting the 

operational objectives of the six reservoirs, and also includes the integrated operation of tributary 

reservoir water control plans so that an effective plan for flood control and conservation 

operations exists within the basin USACE (2006).

Figure 29. Figure displaying the Missouri River Basin in the United States and the six large 

mainstream dams and hydropower facilities (Source: USACE)

As with any federally funded hydropower in the United States, there are multiple uses for these

facilities, with power generation being one of the lowest priorities. These dams were created with 

flood control as their primary purpose, and are also used for navigation, recreation, irrigation, 

and power generation. Furthermore, there are numerous environmental regulations regarding 

water releases from the dams pertaining to bird and fish survival. Combined, these priorities and 

constraints restrict use of the indigenous flexibility available in the hydro generators. Therefore, 

capacity and energy schedules are set subservient to other priority uses and environmental 

constraints. While the dams are operated by USACE, the power is marketed and scheduled by 

WAPA for numerous public power customers. (The power is not available on the Midwest 

Independent TSO market, but rather is dedicated to certain customers for use in meeting their

load). As a result, overlaid on the physical capabilities and constraints of the hydropower 

facilities are numerous organizations and stakeholders. As described in the Master Manual, 

WAPA uses the main stem projects as an integral part of the Midwest power grid. “Project 
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Power Production Orders” that reflect the daily and hourly hydropower limits imposed on project 

regulation are sent to each project on a daily basis, or more frequently, if necessary. Despite this 

complexity and the relative infrequency of the interval for setting the hydropower limits, once 

the capacity and energy schedules are set, there is some flexibility in the use of the hydropower 

by the recipients of the power, but this flexibility is used by each individual power customer and 

not for the overall benefit of balancing the electrical system. 

3.3.3 Summary of River Systems

The foregoing discussion on river systems should have indicated the complexity and 

opportunities found in operating multiple hydropower plants in coordination. Unlike flexible 

thermal power generators, which are primarily “on command” for power generation within their 

physical operating limits and economic dispatch, there are many additional considerations when 

dealing with hydropower. While hydro generators themselves may be quite flexible, the 

availability of their fuel source (water) can be constrained in non-obvious and unique ways, but 

also in ways that can be understood and used in planning.

Regarding future hydropower generation, there has recently been a major emphasis in North 

America and Europe on developing small hydro, particularly because in many jurisdictions only 

small hydro is considered renewable due to the potential impacts of large hydro. Legislation and 

other measures favoring emerging renewable technology and “green” energy therefore often 

exclude “large” hydro, since small projects are perceived as having lower impacts. However, the 

impacts of a single large hydro project must be compared with the cumulative impacts of several 

small projects yielding the same power and level of service. For example, small projects 

generally require a greater total reservoir area than a single large project, to provide the same 

stored water volume. Nevertheless, small hydropower is a necessary and useful complement to 

the electricity generation mix, particularly in rural areas. The most fundamental determinant of 

the nature and magnitude of impacts of hydropower projects are the specific site conditions and 

not the scale of the project. It is also important to optimize development with respect to the 

complete river system.

3.4 Hydropower Generators and Ancillary Services

The purpose of this section is to describe hydropower generators and their use in power plants in 

sufficient detail to understand their capabilities and how they can be used for ancillary services 

and system balancing. Referring to Figure 26, water enters the “penstock” through a grate and 

flows towards the turbine. Somewhere along the penstock, there is a control valve that permits 

flow of water to the turbine and is capable of shutting off the flow. Immediately, upstream of the 

turbine, there is usually a set of “wicket” gates that regulate water flow to the turbine. Turbines 

are able to respond quickly to changes in demand by varying the flow to the turbines through the 

wicket gates. For this reason, AGCs are typically installed onto hydro turbines so that they may

automatically respond to rapid fluctuations in system load and therefore be used for regulation. 

There are three main types of hydropower generators commonly in use today, each capable of 

achieving efficiencies of 80% to 90%: the Pelton, Francis, and Kaplan turbines. The power 

output, P, of these turbines is governed by three basic parameters: the flow rate, Q; the head 

height, h (i.e., the height of the reservoir forebay above the surface of the river immediately 

downstream of the power house); and the efficiency of the generator, η. Written in equation 

form:
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P = Q×h×η×(constant)

Thus, the power output is directly related to Q and h, and the constant shown in this equation is

dependent on the units selected for each parameter (e.g., feet, meters). For any given hydropower 

plant, the flow rate and head height depend on the hydrological conditions and can vary 

substantially from year to year. The type of turbine selected for use at a hydropower plant 

depends on its expected operating conditions. Pelton turbines are employed in situations in which 

the head is high but the flow rate is relatively low. It is an impulse turbine and operates by 

expanding the high-pressure flow the end of the penstock (see Figure 26) through an efficient 

nozzle. The high-speed flow exiting this nozzle is directed at specially designed cups extending 

off a rotor, which receive the flow and redirect it backwards. This process of redirecting the flow 

causes an exchange of momentum between the flow and the rotor, causing the rotor to spin. 

Francis and Kaplan turbines are in very wide use worldwide, and unlike Pelton turbines, are

reaction turbines. Francis turbines can operate efficiently over a broad range of flow rates at 

medium to high head (20- to 100-meters), whereas Kaplan turbines are used primarily in low 

head (run-of-the-river) hydro plants. Reaction turbines operate by expanding the high-pressure 

flow across the blades of the turbine. In doing so, the flow is accelerated over the blades causing 

a low-pressure region on the blade upper surface, efficiently creating lift and causing the rotor to 

spin. While this low-pressure region is germane to its operation, it does have one adverse effect: 

for certain operating conditions, the flow over the blades can cavitate. That is, in the lowpressure region, it is possible for the local pressure to drop below the vapor pressure of the water, 

causing vapor bubbles to form. As the flow exits the low-pressure region of the blade, the vapor 

bubbles collapse and pit the blade. If run for extended periods of time while cavitation is 

occurring, the blade surface will erode, reducing its efficiency and potentially leading to failure 

of the blade and rotor. All reaction turbines have operating conditions that cause cavitation.

Another operation condition that occurs in a reaction turbine is that, under certain conditions, a 

vortex may form in the draft tube causing vibration and damage. Plant operators avoid running 

turbines in these rough zones, as will any automated control systems that may be in place, in 

order to prolong the turbine useful life. The rough zones can extend across a large range of the 

turbine operation. For example, on a 110-MW Francis turbine, it would not be unusual for the 

rough zone to be present for power outputs between 40 MW and 80 MW. Above the rough zone,

generator efficiency is about 85% to 90%, whereas below the rough zone it is between 20% and 

50%.

Large hydropower plants with large reservoirs are often built with several generators. Having 

multiple units in such a hydropower plant gives the plant operator flexibility in choosing which 

units to operate, and the power output level at which to operate them. The same may be true for a 

run-of-the-river power plant, except during times of the year when the river flows are very high 

and the plant is running near its full output. Figure 30 shows a plant efficiency curve for two 

hypothetical hydropower plants with three-generation units each. The efficiency curves are 

steeper for low flow rates (one unit running) and flatten out as more units are operating. The 

implication here to wind/hydro integration is that if the load net wind (or “net load”) causes more 

variations in plant output, the net effect may reduce plant efficiency. Furthermore, if there is also 

greater uncertainty in the generation required to meet the load net wind, this may cause the 

system operator to schedule and dispatch the hydro plant at a lower overall efficiency to allow 

for enough spinning reserve. A reduction in plant efficiency accompanied by an increase in 

cycling of the units will lead to higher operating costs, which would then show up as “wind 
IEA Wind Task 24 Final Report, Vol. 1

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integration” cost, as described in the previous chapter. However, the extent to which this may 

occur and the magnitude of the cost depends on numerous factors and can only be accurately 

estimated via a comprehensive simulation of the hydro and power system operation.

Figure 30. Hypothetical hydropower plant efficiency curves for two different power plants

(Source: B. Smith, Oak Ridge National Laboratory)

An example of a large hydropower facility with several generators is the Hoover Dam located on 

the Colorado River in the Southwestern United States. The Hoover hydropower plant is 

composed of 17 turbines with a total capacity of 2,074 MW. The dam impounding Lake Mead is 

tall and therefore a high head is available to the turbines, most of which are the Francis type 

rated at 130 MW. The capacity factor at the plant is typically on the order of 20% to 30%, 

depending on hydrological conditions. The effect of flow rate on plant efficiency mentioned 

above can be seen in a time-series plot of the Hoover plant efficiency for a day in November 

2007, shown in Figure 31. Note the plant efficiency is higher when the generation requested is at 

a higher level.

Due to their flexibility and the low capacity factor of the plant, the generators at Hoover Dam are 

essentially used for regulation, following the load, and aiding in balancing of the system. Like 

many hydro generators, they are capable of a very high ramp rate, able to ramp at about 75% of 

their capacity per minute (~100 MW per minute). Another screen shot of the Hoover Supervisory 

Control and Data Acquisition is shown in Figure 32. The column on the left-hand side of this 

figure titled “MODE” shows the state in which each of the generators is being operated. The 

generation units at Hoover are typically operated in one of four modes, which are described as 

follows:

1. Standby (STBY): The unit is not generating, but available to be brought online. Typically,

a unit can be brought online within 5 minutes and generating at full power within 10 

minutes (and shut down to full load within 10 minutes).

2. Automatic Generation Control: The unit is online and operating on ACG, providing the 

regulation ancillary service.
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3. Set Point: The unit is online and running at a set power output entered by the operator 

(not shown in Figure 32).

4. Condensing (COND): The unit is being “motored” and run as a synchronous condenser 

providing VAR support to the electrical system. In “motoring” a unit, the wicket gates

supplying water to a turbine are closed and compressed air is injected into the 

compartment (draft tube) housing the turbine rotor, suppressing the water of the tailrace 

(downstream side of the dam) away from the turbine. System power is then supplied to 

the generator’s stator causing it to run as a motor, with the turbine rotor rotating at a 

speed and frequency that allows the unit to be synchronous to the grid.

Figure 31. A plot displaying the Hoover power plant efficiency for a typical day of operation, 

captured by taking a “screen shot” from the Hoover Supervisory Control and Data Acquisition

system (Source: U.S. Bureau of Reclamation, Hoover Power Plant)

MW Requested (Load)

Plant Efficiency
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Figure 32. A “screen shot” from the Hoover power plant Supervisory Control and Data Acquisition

system, showing numerous parameters concerning unit operation (Source: U.S. Bureau of 

Reclamation, Hoover Power Plant)

In addition to these four modes, a unit may also be listed as unavailable (UNAL); for example, if 

it is out of service for maintenance. Figure 32 shows the hour’s capacity schedule was 897 MW, 

the actual generation was 318 MW, and the online capacity was 957 MW. Since the online 

capacity was significantly more than the actual generation, the balance (639 MW) represents 

capacity available as spinning reserve. A typical power production pattern for Hoover power 

plant is shown in Figure 33. As demonstrated in this figure, although the units online at any

given moment at Hoover may be operated to maximize their collective efficiency, the overall 

operating strategy is not to produce the most energy or peak efficiency, but rather to utilize the 

hydropower for the more valuable ancillary services of regulation, load following, and reserves 

(spinning and non-spinning). The Hoover power plant is an example of a very flexible plant, 

within it constraints, and the downstream plants from Hoover are used to re-regulate the flow on 

the river and therefore offer much less flexibility in their operation. Indeed, it is because of these 

downstream facilities that Hoover can be run as it is. 
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Figure 33. A typical production pattern from generators at the Hoover power plant during a day in 

November 2007 (Source: U.S. Bureau of Reclamation, Hoover Power Plant)

As demonstrated in the example of the Hoover power plant, hydropower can provide unique 

benefits to an electrical system. First, when stored in the reservoir behind a dam, it is available 

for use when required. Second, the energy source can be rapidly adjusted to meet demand 

instantaneously. These benefits are known as ancillary services described in Chapter 1 of this 

report, and they include the following: 

1. Spinning Reserve: The ability to run at a zero load while synchronized to the electric 

system; when loads increase, additional power can be loaded rapidly into the system to 

meet demand 

2. Non-Spinning Reserve: The ability to enter load into an electrical system from a source 

not online—while other energy sources can also provide non-spinning reserve, 

hydropower’s quick start capability is unparalleled, taking just a few minutes, compared 

with as much as 30 minutes for other turbines and hours for steam generation

3. Regulation and Frequency Response: The ability to meet moment-to-moment 

fluctuations in system power requirements; hydropower’s fast response characteristic 

makes it especially valuable in providing regulation and frequency response

4. Voltage Support: The ability to control reactive power, thereby assuring that power will 

flow from generation to load

5. Black Start Capability: The ability to start generation without an outside source of power, 

which allows system operators to provide auxiliary power to more complex generation 

Total Capacity Available

On-Line Capacity

Spinning Reserve

Capacity Requested

MW Requested (Load)

Typical Production 

Pattern
IEA Wind Task 24 Final Report, Vol. 1

58

sources that could take hours or even days to restart (systems having available 

hydroelectric generation are able to restore service more rapidly than those dependent 

solely on thermal generation)

3.5 Multi-Purpose Hydro Facilities

In addition to offering clean, renewable energy, hydropower is often only one of a number of 

benefits of a multipurpose water resources development project. Hydropower is generally 

integrated within multipurpose development schemes and can therefore subsidize other vital 

functions of a project. Typically, construction of a dam and its associated reservoir results in a 

number of benefits associated with human well-being, such as secure water supply; irrigation for 

food production and flood control; and societal benefits, such as increased recreational 

opportunities, improved navigation, the development of fisheries, cottage industries, etc. This is 

not the case for any other source of energy. 

When considering the integration of hydropower with other renewable energy, like wind power, 

it is important to recognize that hydropower flows are subject to the many constraints on 

operations, including minimum/maximum flows and minimum/maximum ramp rates. Allowable 

flows are dictated by multivariate optimization considering the following variables:

1. Flood control and safety of structure

2. Fish, wildlife, and other related environmental needs 

3. Irrigation 

4. Navigation 

5. Recreation 

6. Energy/power demands

Often, power needs are not high in priority, and energy delivery must fit into constraints imposed 

by the needs of other systems. Certainly, while the many priorities of a hydro development often 

enable the construction and use of hydropower, they also constrain the flexibility of its use at a 

macro level (e.g., set daily, weekly, or monthly flow requirements, discharge rates, lake levels). 

These constraints depend on the river system and specific hydropower facility, and can vary 

greatly from one hydropower plant to another. Indeed, this is one of the primary reasons it is 

difficult to generalize the results of wind/hydro integration in one system and apply them to 

another, and one of the reasons research Task 24 was formulated. 

3.6 Institutional, Organizational, and Legal Issues Related to Hydropower

The ability to schedule and use the flexibility of a hydropower plant ultimately depends on the 

priorities of the hydropower facility and the organizations that have authority over its operations. 

Due to the multipurpose nature of many hydropower plants and the relationship between hydro 

facilities on a river system, there can be many organizations, agreements, regulations, and laws 

that govern the system. Just as the river systems and priorities of hydropower plants vary, so do 

the organizational and legal frameworks within which they operate. It is this variation that 

differentiates one hydropower system from another, establishing its operating flexibility, and 

distinguishing it from the thermal power resources that can be used for system balancing and 

ancillary services. In the section that follows, an example is provided of the organizational and 
IEA Wind Task 24 Final Report, Vol. 1

59

legal complexity that can surround a hydropower project and define its flexibility for use in 

wind/hydropower integration. It should be noted that this complexity is not necessarily common, 

but that it can and does occur in highly regulated systems.

3.6.1 Example of a Organizational and Legal Complexity: The Colorado River 

System in the United States 

As an example of the organizational and legal complexity that can surround the operation of a 

hydropower plant, essentially defining the flexibility of the generation, consider the Hoover Dam 

and the power plant on the Colorado River in the arid Southwestern United States (see Figure

34). The drainage basin is broken into a two parts: the Upper Basin and the Lower Basin, with 

the division between the two located at Lees Ferry, just downstream of Glen Canyon Dam at the 

head of Lake Powell. Hoover Dam is in the Lower Colorado Basin and impounds Lake Mead, a 

large storage reservoir. The large storage reservoirs along the river can hold up to four times the 

annual average runoff, and serve the important role of delivering water to municipalities and 

agricultural customers throughout the Southwest, assuring water supplies through extended 

drought periods.

Figure 34. Illustration of the upper and lower drainage basins of the Colorado River

(Source: U.S. Bureau of Reclamation)

The U.S. Bureau of Reclamation (Reclamation) has been authorized by legislation to construct 

facilities and produce electric power at Hoover Dam, Glen Canyon Dam, and other smaller 
IEA Wind Task 24 Final Report, Vol. 1

60

facilities along the Colorado River. While Reclamation is the Federal agency responsible for 

water operations and power production at the major dams along the river, WAPA is the Federal 

agency designated to market and deliver this power. WAPA enters into electric service contracts 

on behalf of the United States with 15 public and private utility systems for distribution of 

hydroelectric power produced at Reclamation facilities in excess of project demand. These 

agreements are long-term bilateral agreements in which a power customer receives an allocation 

of the Hoover power and energy, which the customer may not re-market.

Reclamation is part of the U.S. Department of the Interior, and the Secretary of the Department 

is vested with the responsibility to manage the mainstream waters of the Lower Basin pursuant to 

applicable Federal law. The responsibility is carried out consistent with a body of documents 

referred to as the Law of the River.14

The following are particularly notable among these documents:

The Law of the River comprises numerous operating 

criteria, regulations, and administrative decisions included in Federal and State statutes, interstate 

compacts, court decisions and decrees, an international treaty, and contracts.

1. The Colorado River Compact of 1922, which apportioned beneficial consumptive use of 

water between the Upper Basin and Lower Basin

2. The Boulder Canyon Project Act of 1928, which authorized construction of Hoover Dam 

and the All-American Canal, required that water users in the Lower Basin have a contract 

with the Secretary, and established the responsibilities of the Secretary to direct, manage,

and coordinate the operation of Colorado River dams and related works in the Lower 

Basin

3. The California Seven Party Water Agreement of 1931, which, through regulations 

adopted by the Secretary, established the relative priorities of rights among major users of 

Colorado River water in California

4. The 1944 Treaty with Mexico (and subsequent minutes of the International Boundary and 

Water Commission) related to the quantity and quality of Colorado River water delivered 

to Mexico

5. The Upper Colorado River Basin Compact of 1948, which apportioned the Upper Basin 

water supply among the Upper Basin states

6. The Colorado River Storage Project Act of 1956, which authorized a comprehensive 

water development plan for the Upper Basin that included the construction of Glen 

Canyon Dam and other facilities

7. The 1963 United States Supreme Court Decision in Arizona v. California, which 

confirmed that the apportionment of the Lower Basin tributaries was reserved for the 

exclusive use of the states in which the tributaries are located; confirmed the Lower Basin 

mainstream apportionments of 4.4 million acre-feet of water for use in California, 2.8 

million acre-feet for use in Arizona, and 0.3 million acre-feet for use in Nevada; provided 

water for Indian reservations and other federal reservations in California, Arizona, and 

 14 Underwood, D. B., The Law of the River: A Primer, The Metropolitan Water District of Southern California, CLE 

International.
IEA Wind Task 24 Final Report, Vol. 1

61

Nevada; and confirmed the significant role of the Secretary in managing the mainstream 

Colorado River within the Lower Basin

8. The 1964 United States Supreme Court Decree in Arizona v. California, which 

implemented the Court’s 1963 decision; the Decree was supplemented over time after its 

adoption and the Supreme Court entered a Consolidated Decree in 2006 that incorporates 

all applicable provisions of the earlier-issued Decrees

9. The Colorado River Basin Project Act of 1968, which authorized construction of a 

number of water development projects including the Central Arizona Project and required 

the Secretary to develop the Long-Range Operating Criteria and issue an Annual 

Operating Plan for mainstream reservoirs

10. The Colorado River Basin Salinity Control Act of 1974, which authorized a number of 

salinity control projects and provided a framework to improve and meet salinity standards 

for the Colorado River in the United States and Mexico; and the Grand Canyon 

Protection Act of 1992, which addressed the protection of resources in Grand Canyon 

National Park, consistent with applicable Federal law

11. Among other provisions of applicable Federal law, the National Environmental Policy 

Act and the Endangered Species Act of 1973, as amended, provide a statutory overlay on

certain actions taken by the Secretary

With well in excess of 50 laws, acts, or other relevant documents, the Colorado River is highly 

regulated. Furthermore, there are many organizations and regulatory agencies that have a stake in 

how the river is managed. Much of this Law of the River is pertinent to power generation and the 

flexibility of its use, though often indirectly. Indeed, if one were to prioritize the functions 

performed by Hoover Dam, it could be ordered as follows:

1. Flood control / protection of the structure

2. Compliance with environmental regulations and laws

3. Downstream water deliveries

4. Recreation (reservoir water levels downstream of Hoover)

5. Power generation

As is evident, the highest priorities of the dams along the Colorado River system pertain to water 

management, and there are numerous organizations and stakeholders involved in operation of the 

system. With respect to power generation at Hoover Dam, the constraints imposed by its higher 

priority functions result in an allocation of power and energy to Hoover power customers on a 

monthly basis. The power allocation is based on the available head and is typically some fixed 

percentage of the plant capacity, whereas the energy allocation is derived from the expected 

water deliveries from the dam. These allocations are projected approximately 6 months before 

the beginning of the year, and are updated as the year progresses and the actual hydrological 

conditions become known. Due to the many laws and regulations, there is no ability to shift 

usage of the water deliveries from one month to the next for purposes related to power 

generation, and it is necessary that customers use their power allocations within constraints 

dictated by the law. Within each month, however, there is significant flexibility in scheduling 

and use of generators, as was demonstrated in figures in the previous section. Fortunately, the 
IEA Wind Task 24 Final Report, Vol. 1

62

law is implemented in such a way that the flexibility of and constraints on power generation are 

fairly clearly delineated and conveyed to power customers. Furthermore, the two dams 

downstream of Hoover Dam (Davis and Parker dams) are operated to re-regulate the flow out of 

Hoover and to water deliveries, thus facilitating the flexibility at Hoover.

3.6.2 Summary

Once the higher priority functions of a hydro facility or system are satisfied, planning of the 

hydropower can take place, using whatever remaining flexibility is available for use. Authority, 

priority, and markets drive the scheduling of power in an optimized hydro system. Examples of 

ways hydropower systems operate include: operation in an integrated system, where a central 

utility has responsibility to meet electric load growth; or, operation in a more run-of-the river 

mode, with little seasonal or yearly storage capability, governed more by hydropower capacity, 

rather than energy (i.e., more water available than generators to run it through). For cases in 

which a utility may not have load growth responsibility, but owners purchase supplementary 

power for wholesale customers if they request assistance, all additional costs are passed directly 

on to those wholesale customers in near real time. Power may be allocated on a project-byproject basis (rather than system basis) in locations where there is the ability to store water over 

long periods, and output is more energy-limited than capacity-limited. 

Individual institutional situations are important as the context for assessing wind/hydropower 

integration opportunities. For example, in some cases, an individual hydropower resource may 

be developed for the benefit of specific customers, whereas in other cases, a whole drainage 

basin may be operated in an integrated fashion.

Politically, hydropower and other water use allocations are often contentious. Some parties may 

wish to use existing hydropower allocations to support integration of wind energy, where there is 

interest in wind energy development for economic development or other reasons. Other entities 

may see wind energy as a threat to their interests; for example, many utilities with Federal 

hydropower allocations also have large investments in fuel production and other electric 

generating stations, which could potentially be displaced by wind energy generation. With 

numerous potential stakeholders often with opposing objectives, it can be very difficult to 

modify the operating criteria of a given hydro facility and its power plant. Institutional factors 

hinge mainly on the type of control and responsibility held by a hydropower utility or operating 

agency. 

This work concludes that using hydropower to address added ancillary service needs in an 

electrical system with wind power should take account of the flexibility of the hydropower in the 

system. This is because of the complex and often convoluted nature of setting hydro system 

priorities and operating plans. In other words, even amidst the many constraints and multiple 

objectives that may be placed on hydropower generation, there is often a significant amount of 

operational flexibility that still remains. Therefore, the purpose of the many and varied case 

studies that contributed to Task 24 was to consider wind and hydropower integration within a 

system using existing hydropower flexibility. That said, it is not outside the realm of possibility 

to consider modifying hydropower operational criteria or constraints for the benefit of the 

system; however, Task 24 primarily investigates using the existing flexibility of hydro resources, 

as this is perceived to be considerable.
IEA Wind Task 24 Final Report, Vol. 1

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3.7 Variability and Uncertainties of Hydro Resource Across Time Frames of 

Importance in Balancing Area Operation 

A focus of this report has been to discuss the variability and uncertainty in load net wind, which 

is the effective load signal that must be balanced with generation while maintaining transmission 

system reliability. In balancing the system, planners and operators attempt to economically 

optimize system operation, given certain constraints, and amidst uncertainties in load, generation 

availability, wind power, market prices, etc. Understanding the uncertainties and having a good 

sense for the variability in load net wind will aid in managing the resources most effectively. 

Alongside the load net wind, hydropower also has variability and uncertainty related to its 

production, but across different time scales than wind energy. For the time scales of interest to 

system operation and planning, the variability and uncertainty of hydropower is described as 

follows:

Regulation (seconds to 10 minutes):

• There is no uncertainty in hydropower generation (beyond unexpected outages) or 

variability in the hydropower resource on these time scales.

• Hydropower units are typically very agile and responsive to load (or load net wind) 

fluctuations in this time frame. Hydro generators are generally outfitted with AGC and 

are used to keep the system frequency and tie line flows within desired levels. Hydro 

generators also participate in low voltage ride through and VAR support.

Load following (tens of minutes to a few hours):

• There is typically very little uncertainty in hydropower generation or variability of the 

inflows over this time frame. However, uncertainty can be introduced through the flow 

releases at upstream dams in river systems with multiple hydropower facilities.

• Though sometimes constrained due its higher priority functions (limiting flow rates, ramp 

rates, or reservoir levels), hydropower can typically be employed to follow the trends in 

load or load net wind. Generally, the larger the storage reservoir, the greater the ability to 

follow load over longer time periods.

• Hour-ahead forecasting and plant-active power management and scheduling are used.

Scheduling and Unit Commitment (hours to several days):

• Scheduling and unit commitment aims to optimize the mix of generating units to supply 

the hour-by-hour forecasted load at minimum cost (additional reserve units are also 

optimally scheduled).

• Good day-ahead and multi-day forecasting of load (or load net wind) and hydropower is 

key.

• Hydropower plants, especially those with less water storage (on the order of days to 

hours or less), experience uncertainty over this time frame. This can be due to difficulty 

in predicting inflow due to precipitation, or due to interactions on a river system with 

multiple dams. As an example of the latter, refer to Figure 35, which shows a plot of the 

day-ahead flow estimates issued by USACE for Chief Joseph Dam for each day in 
IEA Wind Task 24 Final Report, Vol. 1

64

January 2004. The dark blue line represents the final day-ahead estimate issued by 

USACE, and the thin red line is the actual discharge for that day. The deviation between 

the day-ahead estimated flow and the actual flow is shown by the light green line, which 

refers to the scale on the right-hand side of the plot. Note the percent deviation between 

the estimated flow and reconstructed flow varies between roughly +40% and -15%. This 

significant deviation can be problematic for the system operator of any hydropower 

plants located downstream that rely on this forecast.

• As for the runoff and inflow, these do vary over this time scale. For hydro plants with 

little or no storage, and not embedded in a cascade of hydro dams, this variation can be 

significant. Otherwise, shorter-term inflow fluctuations greatly impact hydro generation. 

The power output of most hydropower plants varies significantly over this time frame; 

however, that variation is typically planned and is in response to market conditions or 

demand, and sometimes other non-power requirements. Therefore, on the order of hours 

to several days, there is little unplanned variation in hydropower production. 

Resource and Capacity Planning (several weeks to years):

• In the time frame of several weeks, hydropower can be very predictable, especially if 

large reservoirs are present in the system. Without large storage reservoirs, the energy 

available can still be reasonably predictable, but depends on the weather, precipitation, 

and overall hydrological conditions. As the planning time frame transitions ahead to a 

year, the uncertainty in hydropower can increase significantly. Hydro systems are 

typically planned a year ahead to a few years ahead by considering many different future 

scenarios for the precipitation. It is common for the year-ahead, firm capacity of a 

hydropower plant to be set based on some historical years of very low inflows, combined 

with what is predicted for the next year based on the current climatologically information. 

In longer time scales covering months to years, hydropower exhibits unplanned variations and 

significant uncertainties. Figure 36 shows an example of the significant inter-annual variations 

that occur in hydropower systems. This figure shows the annual volume of runoff in the 

Colorado River in the Southwest United States plotted over a 100-year period. As seen, there are 

quite significant variations (+/– 50% of the mean flow volume) and the mean flow volume itself 

seems to be changing. As an example of the relative variability of wind and hydropower over 

short and long time scales, Westrick et al. (2003) presented the data shown in Figure 37. The plot 

on the left side of this figure displays the intra-daily volatility as a fraction of plant capacity at a 

hypothetical 100-MW wind power plant at Goodnoe, Washington, U.S., versus the volatility of 

inflow to the 460-MW Ross hydropower facility on the Skagit River, also in Washington (based 

upon a 22-year data record). Obviously, the daily volatility of wind power is quite significant 

compared to the inflow. The right side of Figure 37 shows a plot of the average capacity of the 

wind and hydro plants at these same two locations from May through September, the peak 

months for power demand, over the 22-year data record. Over the time scale of many years, the 

wind power capacity varies about 15%, while the river inflow varies by about 40%. While these 

are only two examples, this type of variation in inflow is common in hydropower systems 

worldwide. The volume of flow that travels down a river annually is related to the amount of 

electrical energy that can be produced. River systems with run-of-the-river type plants will be 

subject to these large variations. Alternatively, large variations in energy produced by 

hydropower plants can be somewhat mitigated by building one or more large reservoirs within a
IEA Wind Task 24 Final Report, Vol. 1

65

river system, capable of holding in excess of 1 year’s runoff. In such a river system, there will 

still be variations; however, they are more to the integral of the annual runoff over 1 or more 

years (depending on the amount of water storage) rather than the yearly precipitation.

The capacity value of a hydro plant (or any power plant) is based on a reliability metric such as

ELCC, and is indicative of the generating capacity that system planners can count on having

available during the peak periods of the year. Hydropower plants can have capacity values on the 

order of 50% to 95%, and the value at any given hydro plant may vary considerably over a 

period of several years due to the variations in annual precipitation, reservoir levels, etc. 

Some hydropower plants with reservoirs that can store multiple days (minimum) to multiple 

years of annual runoff can potentially create new “products” for electricity customers that

essentially repackage wind power into the shape of a more traditional “flat block” purchase. 

These products are often referred to as storage and shaping products. A typical wind storage

product refers to taking wind power into a hydropower system as it comes, then redelivering it at 

some later date (next day, week, month, etc.). The shaping product refers to delivering a flat 

block of firm energy that is equal in energy content to the actual wind power production. 

Bonneville Power Administration in the United States has offered a product like this in the past, 

and Hydro-Québec and Manitoba Hydro have considered creating similar products.

As is evident from this discussion, the variability of hydropower and uncertainties in forecasting 

its production occur primarily over the longer time scales. As a mature technology, these factors 

have been long accounted for in system planning and operation. It is likely that the availability of 

wind energy, which from year to year is less variable than hydropower, may be a complementary 

system energy resource. When considering system flexibility, the ability of hydropower to 

provide regulation, load-following, reserves, and energy storage services will depend on annual 

changes in precipitation. Generally speaking, there will be less flexibility in drought years and in 

flood years, and more flexibility during “normal” years. 

Figure 35. Day-ahead flow estimates versus actual flow from the Chief Joseph Dam in 

Washington, U.S., provided by USACE, for the month of January 2004 (Source: Grant County 

Public Utility District)

0

20

40

60

80

100

120

140

1-Jan3-Jan5-Jan7-Jan9-Jan

11-Jan13-Jan15-Jan17-Jan19-Jan21-Jan23-Jan25-Jan27-Jan29-Jan31-Jan

Flow (kcfs)

-20%

0%

20%

40%

60%

80%

100%

120%

Percent Deviation

Day Ahead Estimate Discharge Percent Deviation
IEA Wind Task 24 Final Report, Vol. 1

66

Figure 36. A time-series plot of the annual flow measured on the Colorado River in the 

Southwestern United States, demonstrating annual and long-term variability (Source: USGS 2004)

Figure 37. The intra-daily volatility of inflow to the Ross hydropower facility and the hypothetical 

power output from a wind power plant at Goodnoe (left), both located in Washington, U.S.; and, 

the average operating capacity from May to September for the same two power plants (right) 

(Source: Westrick et al. 2003)

A broad perspective of the time horizons of interest in a hydro system is shown in Figure 38. As 

displayed, the wind variability crosses several time frames of importance. Whether or not wind 

energy will actually impact any of the issues related to hydro impoundment (blue bars) or

biological communities (green bars) issues is not obvious. However, wind variability and 

uncertainty will affect the hydropower issues (yellow bars) with time frames less than a year and 

especially those less than a week. For example, an unexpected increase in wind output during 

15%

39%
IEA Wind Task 24 Final Report, Vol. 1

67

any given hour (outside the normal bound of the wind forecast error) could affect short-term 

water deliveries if hydro production is decreased to compensate. It is the nature of these types of 

interactions between the wind and the hydro that is the subject of Task 24. 

Strategic 

planning, 

resource 

assessment, 

new projects

Long-term water 

management, 

future valuation 

of water

Wholesale 

energy 

markets

Community 

response

Population 

response

Landscape and 

riverscape adjustment

Water quality variation

Time Horizon (logarithmic scale)

Water temperature variation

Flow and reservoir elevation variation

Precipitation and runoff variation

Increasing 

energy 

demand

Power 

system 

regulation

Turbine hydrodynamics 

and rotor dynamics

Unit operations, 

unit commitment, 

and load allocation

Generation and 

ancillary services 

demands

Increasing 

water 

demand

Short-term 

water routing

Wind Variability

Figure 38. Time horizons of relevance in the hydro system with respect to the hydro impoundment 

(blue), biological communities (green), hydropower (yellow), related to the time scales of wind 

power variability (Source: Oak Ridge National Laboratory)

3.8 Planning of the Hydro System 

Due to the variability of hydropower on the longer time scales, it is necessary for long-term 

planning to ensure sufficient generation is available to meet the load in the months and years 

ahead, especially in drought years. For river systems with numerous power plants and reservoirs, 

there is a need for coordinated planning of the resource. As such, it is common for hydropower 

operators and utilities to participate in joint planning processes and agreements. These planning 

processes will set an overall plan for water operations on the river, complying with any 

environmental requirements and meeting the priority functions of the major dams on the river. 

Results from long-term planning operations may be, for example, a yearly plan of target 

reservoir elevations on a monthly basis for the large storage reservoirs in a system, planning for a 
IEA Wind Task 24 Final Report, Vol. 1

68

possible recurrence of a critical period of historically low stream flows as well as for the flows 

that are actually anticipated based upon best forecasting. Within this broader plan, a more 

detailed plan for operating the hydropower is created, attempting to optimize use of the resources 

available. Utilities or TSOs can then craft their yearly plans for generation. As the year 

progresses and actual hydrology differs from expected hydrology, adjustments are made to the 

plan as well as to the amount of water to be delivered downstream. This allows for updating the

resource and operation plan, allocating excess or securing additional generation resources in the 

monthly-to-annual time frame. These adjustments ensure a balanced load and resource portfolio 

under changing river conditions and needs. 

3.9 Social and Environmental Impacts

Any infrastructure development inevitably involves a certain degree of change. The construction 

of a dam and power plant, along with the impounding of a reservoir, creates certain social and 

physical changes. Difficult ethical issues, such as ensuring the rights of nations to develop, and 

ensuring that the rights of people and communities affected by a project are respected, are also 

likely to arise. The critical action is to explore and anticipate all social and environmental 

impacts early in the planning process so appropriate steps can be taken to avoid, mitigate, or 

compensate for impacts. 

Hydropower has a long history, and lessons have been progressively learned. It is clear that 

many hydro plants in the world have had significant environmental impacts. Today, the 

profession is well aware of the problems to be addressed, and the expertise exists to mitigate the 

known impacts to achieve an acceptable balance—and research is continuing. Reservoirs can in 

fact focus attention on existing problems in a watershed. 

It would be virtually impossible today for a hydro plant of significant size to move ahead without 

detailed studies on its potential impacts being conducted, and a comprehensive report of 

environmental impacts being prepared, including relicensing of existing hydro plants. However, 

the framework, criteria, and degree of public involvement varies from country to country. These 

impact assessments will be an integral part of a multidisciplinary planning approach, and include 

a strong element of public consultation. Environmental Impact Assessments should cover 

positive and negative impacts, both upstream and downstream of a proposed project. These 

impact assessments often also apply to the relicensing of old hydropower facilities.

Once in place, hydropower has a significant positive impact on electrical system operation, 

providing carbon-free energy at low cost, price stability, and flexible generation resources. These 

positive impacts may grow in the future, as hydropower is deployed to enable wind integration.

3.10 Summary: Hydropower as a Balancing Resource and Energy Storage 

The material presented in this chapter describes the salient aspects of hydropower generation that 

are relevant to wind and hydropower generation. The type and magnitude of ancillary services 

and reserves that can be provided by a hydropower plant depend on whether it possesses 

significant storage or if it is a run-of-the-river plant with limited storage. The flexibility of 

operation also depends on whether or not the hydropower is part of a cascade of dams on a river 

system, and the level of coordination between those on the same river. A summary of the various 

types of hydropower plants and their associated ability to provide ancillary services is given in

Table 14.
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Hydro facilities often have numerous functions—power generations being one—that guide their 

operation and define their flexibility. Layered on top of the physical and functional planning, 

there may be numerous organizations and stakeholders involved, along with differing market or 

economic situations. It is the interaction of the many functions, system configurations, and 

stakeholders that establish the authority, priority, and economics that govern the potential for 

wind and hydro integration. 

Thermal power resources are also used for system balancing. Some of those resources, such as 

coal-fired steam power plants, are slowly varying with slowly varying marginal prices. Others, 

such as simple cycle gas turbines, can vary rapidly but also have rapidly varying marginal prices 

that can often be hard to predict. Thermal plants typically are more costly to operate than 

hydropower, and therein lies the main reason and main opportunity for considering hydropower 

as a primary balancing resource in systems that incorporate wind power.

Table 14. Summary of hydro plant storage characteristics and potential for use in provision of 

ancillary services and system balancing

Hydro plant Storage 

Characteristics Description Flexibility for System Balancing and Ancillary Services

Run-of-the-River (no 

storage)

Very small hydro plant, mostly 

domestic or farm level, irrigation 

canals 

Very Little

Hydro with “regulating” 

storage (1–5 hours)

Typically small hydro plant, but 

can have significant generation if 

flow in river is large

Limited potential to handle deviations due 

to forecast errors; regulation and load 

following possible

Hydro with “daily” storage 

(5 hours – 2 days)

Small-to-medium capacity hydro 

projects that may be integrated, 

or in island grids

Useful for load following and regulation; 

can cover some deviations due to 

forecast errors; reserves 

Hydro with “weeks” 

storage (2 days – 2 

weeks)

Medium hydro, but could be large 

hydro with high head and small 

head pond, or part of a large 

hydro cascade 

Effective for regulation, load following, 

and reserves; short-term storage and 

shaping products possible

Hydro with “annual” 

storage (2 weeks – 3 

months)

Medium-to-large hydro Good potential for provision of ancillary 

services and reserves; flexible operation; 

storage and shaping products possible

Hydro with “multi-year” 

storage (3 months to 

multiple years)

Large hydro Excellent potential for provision of 

ancillary services and reserves; very 

flexible operation; storage and shaping 

products possible

Pumped storage Small-to-large hydro Good potential provision of ancillary 

services and reserves; storage and 

shaping possible if a large reservoir

The overarching question for studying wind and hydropower integration is whether systemoperating impacts due to wind power can be accommodated by hydropower within the

constraints currently in place on hydropower (or not easily changed), and in an economically 

advantageous way. And if so, what changes will this cause to hydropower operations or costs? In 

concept, hydropower should be able to provide short- to medium-term buffering of the enhanced 

variability and uncertainty wind power induces in the overall load net wind. Adding wind power 
IEA Wind Task 24 Final Report, Vol. 1

70

to the system may or may not help hydropower meet power and other system demands, and the 

influence on other hydro functions, such as water deliveries, must be considered. That said, even 

within the constraints currently imposed on hydropower, it is a valuable system balancing 

resource, and possesses the inherent qualities needed to facilitate wind integration. The case 

studies performed as part of Task 24 were intended to provide some insights into wind and hydro 

integration, demonstrating the level of its feasibility for a variety of different hydro, wind, and 

electrical system configurations.
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4 Power System Planning and Operation in Systems with Wind 

and Hydropower

4.1 Introduction

Chapter 1 of this report introduced the aspects of electric system operation and planning that are 

of most relevance to wind integration: utilities and markets, ancillary services, and system 

planning and operation. It provided the vital background necessary to understand the reasons for 

forming Task 24, described the objectives and questions being addressed, and presented the 

members and work plan of the task. Chapters 2 and 3 went on to provide descriptions of wind 

power and hydropower, respectively, discussing the aspects of importance to the Task 24 

objectives and expected results. Chapter 2 presented a perspective on the value of wind energy, 

and then described in detail the characteristics of wind power variability and uncertainty, their 

relationship to power system operation and planning, and wind power’s contribution to system 

capacity. Chapter 3 provided an overview of hydropower, and then discussed in detail aspects of 

hydro system operation and planning relevant to electrical system operation and planning. Of 

particular importance were aspects of hydropower of importance to wind integration. The 

chapter concluded with a summary of issues related to hydropower as a balancing resource and 

for energy storage. The material presented suggests that systems with hydropower may be well 

suited to incorporate wind power, due to the potential for synergistic operation of wind and 

hydropower facilities within or across balancing areas. However, though inherently flexible, 

hydropower possesses unique operating constraints and complexities that make it unclear that 

integration with wind power is advantageous or even practical in some cases. As a consequence, 

there are many misconceptions about the feasibility of wind/hydro integration across a range of 

issues: its impacts on system operation and balancing including costs to address these impacts; 

its economic feasibility; its impact on the transmission system and system reliability; and its 

effect on spill and hydropower constraints (in particular, non-power constraints due to 

environmental considerations).

The purpose of the present chapter is to describe power system operation and balancing in 

systems with wind power and hydropower, drawing upon the Task 24 case studies and other 

relevant literature. At the end of Section 1.2, a set of questions were presented that motivated the 

formation Task 24. These questions and outcomes are addressed in the subsections to follow,

which include an overview of important results from recent wind integration studies, a review of 

the information summarized in the “State-of-the-Art” report produced by IEA Wind Task 25 on 

the “Design and operation of power systems with large amounts of wind power” (Holttinen et al. 

2008), and a summary of the Task 24 case studies and their findings related to the Task 24 

questions and expected outcomes (refer to Section 1.3.5).

4.2 Wind Power Impacts in Systems with Hydropower

4.2.1 Results from Recent Wind Integration Studies

Wind integration efforts have been conducted in an assortment of electrical system balancing 

areas across the globe, in systems ranging from small to large, using a variety of methodologies, 

at different wind penetration levels in a variety of power system structures (e.g., market systems, 

generation fleets). Over the past several years, common methodologies have arisen as a result of 

industry experience with wind integration studies. Depending on the information sought in a 
IEA Wind Task 24 Final Report, Vol. 1

72

study, techniques ranging from simpler, purely statistical techniques, to more complex cost 

production simulations that model transmission system constraints and the decisions made in 

operation of the power system. An overview of these methodologies is provided in Volume 2 of 

this report, Section 1.1. Almost regardless of the method, the impacts of wind integration are 

deduced by comparing operation of the system to meet load demand compared to meeting the 

load demand less the wind power (load net wind or net load). Furthermore, it is crucial in 

analyzing wind integration impacts and costs that the system (balancing area) be considered in 

whole, or some transmission constrained subset of the balancing area. In performing a study, 

whether simple, detailed, or evolutionary (as discussed in Volume 2, Chapter 1), it is important 

to consider the effect of wind integration on the entire balancing area, and not to consider a wind 

power plant in isolation (for example, to try to create a flat output from a single wind power 

plant by “firming” it with hydro or other type of power). With this system-wide perspective, the 

wind integration cost is defined as the difference in cost to operate the system with increased 

variability and uncertainty due to wind power versus cost to operate the system in some fashion 

without those influences. 

There are now a large number of studies related to wind integration and interconnection in the 

literature. A listing of a majority of these studies, in excess of 670, is in the bibliography 

provided in Appendix A. The reports are organized by country of origin, and author/title, with a 

link to the report if available on-line. Of these many reports, a small subset are comprehensive 

reports that describe complete wind integration studies and present wind integration costs. Wind 

integration costs are generally reported as ancillary services costs attributed to the addition of 

wind power to current system operations, typically reported as an incremental integration cost at 

various levels of wind penetration. 

Table 15 gives a summary of integration costs from several U.S. studies (Wiser 2009). These 

costs are not unlike those found in studies outside the United Sates, where the total integration 

costs are on the order of 1/10th the cost of the wind energy itself. As presented here, the

integration costs relates to the bottom section of the red bar shown in Figure 7. Note the wind 

capacity penetration is listed as a key parameter in differentiating the studies shown in the table. 

There are a number of potential methods to define the wind penetration (see Volume 2, 

Section 1.2); in this table, it is defined by dividing the nameplate wind power capacity by the 

peak load of the system. 
IEA Wind Task 24 Final Report, Vol. 1

73

Table 15. Wind integration costs in U.S. dollars per MWh of wind energy produced from several 

recent studies in the United State (Source: Wiser 2009)

4.2.2 Review of Results from IEA Wind Task 25

As described in Chapter 1, integration of wind power into power systems is an active area of 

research and, as pointed out previously, there have been numerous publications related to the 

topic including some produced by the IEA (e.g., IEA 2005, IEA 2008a). IEA Wind established 

R&D Task 25 in 2005 on the “Design and Operation of Power Systems with Large Amounts of 

Wind Power.” This task deals specifically with issues related to wind integration impacts, costs, 

and analysis techniques. Tasks 24 and 25 bear many similarities centered around wind 

integration, but Task 24 focuses on systems with hydropower. Because it is of bearing here, and 

because there is no desire to repeat the good work accomplished in Task 25, a summary of some 

of the key findings from Task 25 as presented in the “State of the Art” report (Holttinen et al. 

2008) and relevant to Task 24 will be presented here. These results are generally applicable to 

systems with and without hydropower, though they do not include the focused study on 

hydropower interactions that are part of the Task 24 case studies. Following this section, the 

findings of the Task 24 case studies that specifically deal with systems with hydropower will be 

presented. 

In Task 25, the integration costs were divided into components originating from grid expansion 

costs and operational balancing costs. Grid expansion costs are attributed to costs arising from 

grid reinforcements or expansions required to deal with handling large power flows and 

maintaining stable voltages, which are particularly of importance in weak grids where the 

generation is located far from load centers (common for wind power plants). Because this issue 

is independent of whether the system has hydropower or not, it will not be addressed here. The 

operational balancing costs, however, are dependent upon whether or not the system has 

hydropower, and how the hydropower is modeled and deployed in simulating these systems. The 
IEA Wind Task 24 Final Report, Vol. 1

74

results of Task 25 were based upon studies conducted in 22 wind integration studies contributed 

by members of the Task, as summarized in Table 16. 

Table 16. Power system size and wind power penetration studied in national cases 

(Source: Holttinen et al. 2009)

Load

Interconnect 

capacity

Wind Power

2008 Highest 

Studied Highest Penetration Level

Region /

Case Study

Peak 

MW

Min 

MW TWh/a MW MW MW TWh/a

% of 

peak 

load

% of 

gross 

demand

% of (min 

load + 

interconn)

West Denmark 

2008 3,700 1,300 21 2,830* 2,380 2,380 5 64 % 24 % 58 %

Denmark 2025 a) 7,200 2,600 38 5,190* 3,150 6,500 20.2 90 % 53 % 83 %

Denmark 2025 b) 7,200 2,600 38 6,790* 3,180 6,500 20.2 90 % 53 % 69 %

Nordic /VTT 67,000 24,000 385 3,000* 4,772 18,000 46 27 % 12 % 67 %

Nordic+Germany/

Greennet

155 

500 65,600 977 6,600* 28,675 57,500 115 37 % 12 % 80 %

Finland/VTT 14,000 5,900 90 2,280* 143 7,300 16 52 % 18 % 89 %

Germany 

2015/Dena 77,955 41,000 552.3 10,000* 23,903 36,000 77.2 46 % 14 % 71 %

Ireland/ESBNG 6,500 2,500 38.5 0 1,002 3,500 10.5 54 % 27 % 140 %

Ireland / SEI 6,900 2,455 39.7 900* 1,002 1,950 5.1 28 % 13 % 58 %

Ireland 2020/All 

island 9,600 3,500 54 1,000 1,002 6,000 19 63 % 35 % 178 %

Netherlands 25,200 9,000 127 7,350 2,225 10,000 35 40 % 28 % 61 %

Mid 

Norway/SINTEF 3,780 21 1,062 3.2 28 % 15 %

Portugal 8,800 4,560 49.2 1,000 2,862 5,100 12.8 58 % 26 % 92 %

Spain 2011 53,400 21,500 246.2 2,400 16,754 17,500 46 33 % 19 % 73 %

Sweden 26,000 13,000 140 9,730* 1,021 8,000 20 31 % 14 % 35 %

UK 76,000 24,000 427 2,000* 3,241 38,000 115 50 % 27 % 146 %

Minnesota, U.S., 

2004 9,933 3,400 48.1 1,500* 1,752 1,500 5.8 15 % 12 % 31 %

Minnesota, U.S., 

2006 20,000 8,800 85 1,752 6,000 21 30 % 25 % 68 %

New York, U.S. 33,000 12,000 170 7,000* 882 3,300 9.9 10 % 6 % 17 %

Colorado, U.S. 7,000 36.3 1,068 1,400 3.6 20 % 10 %

California, U.S. 64,300 25,000 304 2,517 12,500 34 19 % 11 %

Texas, U.S. 65,200 16,000 317 7,116 15,000 54 23 % 17 %

* The use of interconnection capacity to countries outside the modeled area is not taken into account in these studies. In 

the Nordic 2004 study, the interconnection capacity between the Nordic countries is taken into account. In 

Nordic+Germany/Greennet study the 5 modeled countries are divided into 12 regions interconnected by transmission lines, 

thereby including the influence of interconnection capacity between countries within the modeled area.

A summary of the Task 25 results for increase in balancing requirements, presented as a increase 

in reserve requirement as a percent of the increase in wind capacity is shown in Figure 39. The 

results here indicate that as the wind penetration increases, the percent reserve requirement also 

increases, and that the increase is below 10% in all cases. The costs associated with the increases 
IEA Wind Task 24 Final Report, Vol. 1

75

in reserve requirements for several studies are shown in Figure 40. These costs are consistent 

with those presented in Figure 39, and also indicate that as the wind power penetration increases, 

the costs to handle the ancillary services (reserves) also increase per megawatt-hour of wind 

energy produced. In interpreting these results, and in particular the spread in the results, it is 

important to understand that there are differences in the study methods employed, the wind 

resources, the system operational characteristics, and the load. 

Regardless of the differences between the various studies presented, some general conclusions 

could be drawn:

• Spreading the wind power over a large geographical region tended to smooth out the 

variations and reduce the integration costs.

• If the interconnections with neighboring systems were permitted to assist in balancing the 

system, then wind integration costs were reduced.

• Allowing for changes in schedule to be made closer to the delivery hour tended to decrease 

integration costs. 

Of importance in all these studies were the size of the system and the inherent flexibility of the 

generation fleet and operational setup to deal with system uncertainties and variations in net 

load. The more flexibility a system possesses, the more aptly it can deal with the variability and 

uncertainty of wind energy.

Increase in reserve requirement 

0 %

2 %

4 %

6 %

8 %

10 %

12 %

14 %

16 %

18 %

20 %

0 % 5 % 10 % 15 % 20 % 25 % 30 %

Wind penetration (% of gross demand)

Increase as % of wind capacity

Nordic 2004

Finland 2004

Sweden 1 hour

Sweden 4 hours

Ireland 1 hour

Ireland 4 hours

dena Germany

Minnesota 2006

California US

UK, 2007 distributed

wind

Figure 39. Results for the increase in reserve requirement due to wind power 

(Source: Holttinen et al. 2009)
IEA Wind Task 24 Final Report, Vol. 1

76

Increase in balancing cost 

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

0 % 5 % 10 % 15 % 20 % 25 % 30 %

Wind penetration (% of gross demand)

Euros/MWh wind

Nordic 2004

Finland 2004

UK, 2002

UK, 2007

Ireland

Colorado US

Minnesota 2004

Minnesota 2006

California US

Pacificorp US

Greennet Germany

Greennet Denmark

Greennet Finland

Greennet Norway

Greennet Sweden

Figure 40. Results from estimates for the increase in balancing and operating costs due to wind 

power; the currency conversion used here is 1 € = 0.7 £ and 1 € = 1.3 $ U.S.

(Source: Holttinen et al. 2009)

Another important consideration that was investigated in Task 25 was the capacity value/credit 

of wind power. Many system expansion plans are developed around the need for peak capacity, 

and therefore the capacity that a resource can be relied upon during the peak hours of the year 

(e.g., the ELCC) is vital. A summary of the capacity credit attributed to wind power for several 

of the Task 25 case studies is presented in Figure 41. The capacity credit tends to be higher at 

low penetrations of wind power, and range from a high near the capacity factor of the wind 

power plant to 5% at high levels of wind penetration (> 30% of gross demand). 

Capacity credit of wind power

0 %

5 %

10 %

15 %

20 %

25 %

30 %

35 %

40 %

45 %

0 % 10 % 20 % 30 % 40 % 50 % 60 %

Wind power penetration as % of peak load

Capacity credit

Germany

Mid Norway 3 wind farms

Mid Norway 1 wind farm

Ireland ESBNG 5GW

Ireland ESBNG 6.5GW

UK 2007

US Minnesota 2004

US Minnesota 2006

US New York on-off-shore

US California

Figure 41. Capacity credit of wind energy as computed in several of the Task 25 case studies

(Source: Holttinen et al. 2009)

4.2.3 Wind Integration in Systems with Hydropower: Summary of Results from 

Participant Case Studies 

Volume 2 of the Task 24 Final Report deals primarily with the wind/hydro integration study 

methodologies and presents the case studies performed by each of the participating 

organizations. Each of the case studies addressed a subset of the questions posed in forming the 
IEA Wind Task 24 Final Report, Vol. 1

77

Task. In this section, a short description of each case study is provided followed by the key 

results pertaining to the task work plan. Study presentations are organized by the country of 

origin. More detail on these studies can be found in Volume 2. 

4.2.3.1 Australian Case Studies

Hydro Tasmania is Australia’s leading renewable energy business, providing renewable energy 

to the national grid and trade energy and environmental products in the National Electricity 

Market. The studies in this section are based on Hydro Tasmania’s power system. Because of the 

potential for significant integration of wind power into the hydro-dominant Tasmanian power 

system, or provision of ancillary services to the greater Australian system (load net wind), Hydro 

Tasmania carried out the following three studies to address various aspects of wind integration.

Case Study 1: Large-scale wind integration to the Tasmanian system

Case Study 2: The costs of wind-firming service provided by a hydro plant

Case Study 3: Inertia support in a hydro, wind, and high-voltage direct current (HVDC)

hybrid power system

For the purposes of these studies, Hydro Tasmania’s system was modeled with 1,850 MW of

peak load, a 900-MW minimum load, and 630-MW/480-MW export/import capability via an 

HVDC interconnect with the Australian mainland. Conventional generation comprises mostly 

hydropower generation with a mixture of storage and run-of-the-river schemes (2,267 MW). The 

installed capacity of thermal generation is 400 MW, and the capacity of wind generation is 

140 MW. The HVDC interconnector links the Tasmanian power system to the four-state network 

on mainland Australia. The Tasmanian power system is small in comparison to its largest 

generator (210 MW) or load (200 MW), and the frequency standards have been recently 

tightened for a single contingency to 48.0–52.0 Hertz. System capacity is managed in the shortand medium-term through the Projected Assessment of System Adequacy. This covers a 2-year

window of power generation and consumption. Daily dispatch is undertaken as a 24-hour predispatch followed by a 5-minute look-ahead during actual dispatch. The Australian National 

Electricity Market is a spot market based on 5-minute dispatch intervals (and bids). The market

price is set by the marginal generation bid. The market objective is to supply energy at the least 

cost; practically, this is a constrained least cost due to the limited physical capability of the 

power system. There is a co-optimization between the spot energy market and the FCAS market. 

The FCAS market and the mechanism by which constraints apply to the energy market is the 

focus of these studies.

Case Study 1: Large-Scale Wind Integration to the Tasmanian System

Case Study 1 had the objective of identifying limits for the penetration of wind generation in 

Tasmania based on power system performance. The initial studies concluded that in order to 

ensure the security of the power system with a minimum system load of about 900 MW, together 

with 300 MW of import to Tasmania through the (then) proposed Basslink HVDC 

interconnector, wind generation would have the following implications:

• Between 130 MW and 150 MW of wind generation would require very little change in 

system operation.
IEA Wind Task 24 Final Report, Vol. 1

78

• Operation with between 150 MW and 300 MW of wind generation would require increased 

FCAS (balancing15

The more recent 2009 Transend Study shows that up to 1,300 MW of wind generation could be 

incorporated into the Tasmanian system with Basslink in service if mitigation measures are put 

in place to support system interia. This figure reduces to approximately 620 MW with Basslink 

out of service. In both cases, higher wind penetrations would occasionally require wind 

generation curtailment. Current minimum system inertia is between 3,500 MW and 4,000 MW. 

Under the new frequency operating standards for Tasmania, system inertia will need to be 

maintained above the current minimum. Because there are many hydro generators in Tasmania 

that can operate in synchronous condenser mode, one possible mechanism is to bring generators 

online in this mode when inertia falls below minimum levels. Synchronous condensers are 

traditionally used for voltage control support; however, they also provide inertia and fault 

contribution to the system as added benefits. Where new supplementary voltage control 

equipment or dynamic reactive power sources are required, synchronous condensers should also 

be considered in place of power electronic devices (e.g., switched virtual circuit, static

synchronous compensators), which do not provide inertia and fault contribution.

) operation from conventional synchronous plant or advanced wind-plant 

control systems.

Case Study 2: The Costs of Wind-Firming Service Provided by a Hydro Plant

Case Study 2 evaluated the impact on the storage system of installed wind generation, assuming 

coordinated operation. Two systems are investigated, including operation of an islanded system 

and an interconnected system within the Australian mainland. For an isolated system, the wind 

displaces hydro generation—during wet, windy periods this results in a considerable increase in 

spill. The interconnected system provides much better opportunities for additional wind 

generation to either be stored or exported to the mainland system without incurring spill. For the 

purpose of this study, wind firming implies the service of supporting wind power production that 

is assumed to have a “firm” 40% capacity factor (40% is a typical, if not low, capacity factor for 

a Tasmanian wind resource).16

Interconnected operation reduces monthly spill of generated energy from 30–50 GWh to less 

than 2 GWh. The annual spill of hydro energy varies between 50 GWh per year to 200 GWh per 

annul under isolated operation. This amount is reduced to approximately 10 GWh per year with 

If the wind production falls short of 40% capacity during any 

given hour, the energy shortfall between hourly wind generation and firm capacity is valued at 

the spot market price. Wind energy in excess of the firm capacity is sold into the market. Thus, 

wind firming refers to the service of guaranteeing a firm capacity from the wind power 

production on a yearly basis, via use of the hydro storage system (either storing water when wind 

is in excess of its firm capacity or spilling if necessary, and using water for generation when 

wind production falls short), with energy transactions valued at the spot market price. Two 

systems were considered: the first covering an isolated operation of a Tasmanian system and the 

second covering interconnected operation. The study focused on the efficiency of water storage 

and spill control.

 15 In the Australian National Electricity Market, the balancing function is provided by FCAS products offered into a 

5-minute market and co-optimised with energy. 16 It is worth noting that most utilities do not sell wind energy as “firm” capacity. A few, however, do this as can be 

of value to the purchaser if the capacity of the wind is guaranteed (versus simply taking the energy that the wind 

produces, whether less than or more than the annual capacity factor during any given hour).
IEA Wind Task 24 Final Report, Vol. 1

79

interconnected operation. Even with 500 MW of wind generation, interconnection reduces the 

spill to about 100 GWh after 10 years. The same spill would have occurred with less than 100 

MW of wind generation in a case of isolated Tasmanian system operation.

Isolated Tasmanian System

In the case of islanded operation of a Tasmanian power system, the system is unable to 

effectively absorb all output from large-scale wind generation due to coincident of high winds 

and high inflows. There is an increasing negative impact on storages as wind generation capacity 

is increased. The system energy yields (hydro and wind) in the first quarter of the year critically 

determine how large this effect is. Also, the coincidence of high wind and hydro inflows in the 

period between September and November led to a small increase in spill. Coincidence of low 

wind and hydro inflows in the period between February and June resulted in a greater 

requirement on the hydro system to meet load when storages are low. Under such conditions, 

there may be minimal reduction of using stored water.

Tasmanian System Interconnected with Mainland

The addition of the high capacity interconnection (HVDC, 600-MW export and 480-MW import) 

with Australian mainland is a major improvement, allowing the ability to significantly increase 

penetration of wind generation in Tasmania without a negative effect on the energy in storage. A 

small increase in system spill is noted. The expected marginal cost of “firming up” wind 

generation can be as high as $14AUD/MWh at 500-MW installed capacity. Firming of wind 

increases the average production costs of wind power by $3 AUD /MWh in a case of 100-MW 

wind development, and $8AUD /MWh in a case of 500-MW wind power development.

Case Study 3: Inertia Support in a Hydro, Wind, and HVDC Hybrid Power System

Case Study 3 focused on operating issues typical for a small system. The main issue is the effects 

of large-scale wind generation displacing hydro generators and resulting in very low system 

inertia and an associated high rate of change of the frequency during system disturbances. The 

study identified that the limiting factors in developing wind generation in Tasmania are due to 

low system inertia and very fast frequency changes affecting the operation of back protection 

schemes (i.e., under-frequency load shedding). The report also identified that commitment of 

additional hydro generators operating in either synchronous condenser mode or tail water 

depression mode can largely improve the integration of the wind generation in Tasmania. In 

particular, the use of tail water depression mode allows fast machine start up from motoring 

operation and provides three valuable services including voltage/reactive power control, 

additional inertia, and additional FCAS. However, at present, inertia is not a recognized market 

service and the work on recognition of this service is not accepted as an off-market service, as is 

the case for reactive power support.

Large penetration of wind generation in the isolated hydro system would result in commitment of 

fewer hydro generators under strong wind conditions. Also, generators in service would operate 

at lower than efficient output. This situation is made more difficult with the HVDC 

interconnector. Recent experience in Tasmania shows that some generators operate at output as 

low as 10% to increase system reserves (i.e., FCAS) and to make the system heavier (i.e., add 

inertia).
IEA Wind Task 24 Final Report, Vol. 1

80

The cost of low output operation is high due to low efficiency. Increased cavitation damage and 

higher maintenance requirements have also been reported. The cost of supplying additional 

inertia in the hydro-based system with machines capable of operation as synchronous condensers 

or in tail water depression mode is low in comparison with the potential benefits. The cost of 

motoring relates to a load of about 2% of machine rating. These benefits include the following:

• Allows maximization of inter-connector flows

• Allows greater fraction of inertia less generation (variable speed doubly fed induction 

generator wind generation) in Tasmania

• Improves efficiency of using water comparing to low load operation

• Reduces maintenance requirements on hydro units

4.2.3.2 Canadian Case Studies

Natural Resources Canada, Hydro Québec, and Manitoba Hydro all participated in Task 24 on 

behalf of Canada. For reasons associated with utility approval to release detailed study 

information, neither Manitoba Hydro nor Hydro Québec were able to contribute case study 

reports to the Task 24 final report, though they were routine contributors at the R&D meetings. 

Natural Resources Canada did conduct a study and contributed it to the task, as described below. 

Its study focused on the economic impact and feasibility of incorporating wind power to cover 

load growth using its RETScreen17

The RETScreen analysis sought to evaluate the economic effects of integrating wind generation 

into Okanogan PUD in Washington State, U.S., a small, hydro-dominated utility that is often 

required to purchase power from the market to supplement the scheduled resources. Okanogan 

PUD purchases all of its power, approximately 60% of which is supplied by the Bonneville 

Power Administration and 30% by the Wells Hydroelectric Project. The purpose of the study 

was to determine if the additional energy procured by wind at the proposed rate would be

economically favorable to purchasing power from the market when supplementary amounts are 

needed. Particular attention was paid to wind resource availability during times of drought, when 

hydro resources are strained and market prices tend to be higher. This study differs from most of 

the other case studies that have been contributed to Task 24; it is an economic evaluation of 

incorporating wind energy into a system versus other alternatives (an estimate of the value of 

wind energy), and not a grid integration study that seeks to determine the impacts and costs of 

wind power’s variability and uncertainty.

project analysis tool.

The Okanogan PUD system has a dual peak in the winter and summer of approximately 

145 MW. Its average load is about 90 MW (based on an assumed 60% system load factor). Its 

generation resources are almost entirely hydroelectric (86%) with several flow restrictions 

through dams located on the Mid-Columbia River. Okanogan PUD was interested in acquiring 

25% of the power output from the 64-MW Nine Canyon Wind Farm project. On a capacity basis, 

this amounts to about 16 MW, or 11.4% of the peak system load levels of 140 MW. On an 

energy basis, this would amount to approximately 7% of the annual energy requirement for the 

utility, given an estimated capacity factor of 31.4%. 

 17 See http://www.retscreen.net/ang/home.php; RETScreen stands for Renewable-energy and Energy efficient 

Technologies Screening tool, and was develop for Natural Resources Canada.
IEA Wind Task 24 Final Report, Vol. 1

81

Wind variability is smoothed/handled by the Load Control Area operator for Douglas County 

PUD at the Wells Dam on the Columbia River. This also allows Okanogan PUD’s share of the 

wind power to be delivered at a later time. The study found that the amount of wind being 

integrated from the Nine Canyon Project would lead to minimal need for additional ancillary 

services, as fluctuations in wind power production would hardly alter the utility’s existing load 

swings.

The conclusions of this study offered a comparison of the parameters that were predicted by the 

RETScreen analysis and those that were encountered in reality. The actual wind power delivered 

over the 3-year period of 2003–2005 was about 90% of that predicted to be normal by the 

RETScreen procedure. The net cost of delivered wind energy during this period was $44.1

CAD/MWh, which exceeded the cost of $43.9 CAD/MWh that would have been accrued if the 

energy had been purchased from the market. This negative value was made up for when the 

utility sold Renewable Energy Credits during 2005 for $3 CAD/MWh, resulting in a positive net 

value of $37,000 CAD for the wind power over the 3-year period. The report also concluded that 

the wind purchase would not have been economically favorable without the Renewable Energy 

Production Incentives. 

The study highlighted results showing the ease of integrating wind into a hydro-centered Load 

Control Area, as balancing costs were kept at $0.9 CAD/MWh instead of the $4.5 CAD/MWh 

that would have been required for purchasing balancing services from Bonneville Power 

Administration. It suggested that there would be minimal requirements for additional ancillary 

services due to wind because the Load Control Area operator easily smoothed fluctuations by 

using hydro flexibility. For the years studied, a positive correlation was found to exist between 

periods of drought and low wind for the region. This corresponded to an increase in both the cost 

and value of available wind power. However, market prices were also found to be higher during 

these same periods, helping to maintain the economic position of purchasing wind power.

4.2.3.3 Finnish Case Studies

The Technical Research Centre of Finland (VTT) conducted two case studies on behalf of 

Finland:

• A case study focusing on the handling of wind power prediction errors for a single 

hydrothermal power producer in Finland 

• A summary of the impacts of a wind- and hydro-dominated power system on the electricity 

markets and the characteristics of Nordic hydropower

For the purpose of these studies, the word regulation is used to mean 10–15-minute balancing, 

and balancing market refers to what is officially called the Regulating Power Market in the 

Nordic countries—the more neutral word balancing is also used.

Case Study 1 was performed to see the possibilities of a hydrothermal power producer with 

limited regulation possibilities to balance wind power in its portfolio. This case study is based on 

one producer using the Nordic electricity market. The producer has 400 MW of run-of-the-river 

hydropower with very limited storage possibilities. Wind power generation is forecast 1 day 

ahead, and balancing can be done at the market (paying imbalance prices of forecast errors; part 
IEA Wind Task 24 Final Report, Vol. 1

82

of the forecast errors can be dealt with intra-day trade) or by the producer internally by adjusting 

hydropower production.

The case study was based on 1 year of data. A time series of forecast errors for 9 MW of wind in 

2004 was increased to 200 MW and 400 MW of wind power (representing 50% and 100% of the 

hydro producer’s installed capacity, respectively). The first step in the study was pricing 

imbalances at current Nordic market rules (2004 price data). The second step was using 2004 

prices for intra-day market pricing (closing 1 hour before delivery) to calculate how intra-day 

trading would reduce imbalance costs. The third step was looking at the possibilities of 

hydropower to handle the imbalances, which was done by looking at the time series of produced 

hydropower in 2004 and calculating how much of the forecast errors of wind could be corrected 

by shifting hydropower production some hours. Limits for minimum and maximum hydropower 

production were kept the same, and the total energy for each day was kept at ±10 % of the 

original time series.

Wind power penetration in Finland was less than 1% of gross demand (energy) and less than 3% 

of peak load (capacity). Two wind power scenarios, 200 MW and 400 MW, were studied, which 

were 50% and 100% of the producer’s installed hydropower capacity. The study assumed that 

wind power in Finland (200–400 MW) would not affect the market and balancing market prices. 

A limitation of the study is that a simulation was not performed to estimate how much 

hydropower energy could be shifted from 1 day forward.

The study concluded that the imbalance costs from day-ahead forecast errors for aggregated 

wind power in Finland is roughly € 0.62 /MWh, when calculated per megawatt-hour total 

produced. The cost of regulation, when there is an extra cost, is on average € 3–4 /MWh. But, 

more than half of the time, the wind power imbalance is opposite to the total system imbalance. 

For those hours, the only cost effect is the fixed volume cost of € 0.7/MWh for the imbalances. 

These results apply for the Finnish power system in which wind power is not affecting the price 

level or direction of regulation used in the power system. Also, the balance settlement rules 

affect the results—the use of a one-price model instead of a two-price model would drop the 

balancing costs to near zero.

Compared with leaving all day-ahead forecast errors to balance settlement, Elbas trading is only 

cost effective when trading close to spot price levels (Elbas is an intra-day market to cover 

anticipated imbalances between the load and generation, see Figure 5). Actively trading to 

reduce the forecast errors of wind means making trades almost all the time. Leaving the forecast 

errors to imbalance settlement means that more than half of the time there is no penalty. 

Approximately 60% of the time, there is only a € 0.7/MWh volume fee for the imbalances; 

usually the Elbas trade is not cost effective. Additionally, 400 MW of hydropower could provide 

internal balancing to correct 83% of prediction errors for 200 MW of wind power. For 400 MW 

of wind power, 63% of the imbalances could be balanced internally. Using hydropower to 

balance wind power imbalances is profitable for both parties. Depending on the price set for the 

internal balancing and the wind power capacity, the balancing costs for the wind power producer 

would be reduced by roughly 20–85%.

This study showed that even with the limited flexibility of hydropower (run-of-the-river with 

small reservoirs), a large part of wind power forecast errors can be provided for by shifting 
IEA Wind Task 24 Final Report, Vol. 1

83

hydropower back and forth inside 1 day. This is because the wind power forecast errors average 

zero, so both up- and down-regulation are used and the side of balancing varies from up to down 

and back frequently. The study also showed that when correcting the forecast errors of wind 

power at a large balancing market in which hydropower produces most of the balancing (like in 

Nordic countries), there is not a great benefit of combining/integrating wind power and 

hydropower at a single producer. It is more cost effective to bid all flexibility of hydropower to 

the balancing market and use it from there to correct the system imbalances than to use it for 

dedicated balancing of wind power.

The second Finnish case study analyzed the impacts of a wind- and hydro-dominated power 

system on the electricity markets and the characteristics of Nordic hydropower. In reference to 

the intended outcomes of the report relative to the objectives of Task 24, the market model 

WILMAR was used to model the behavior of the Nordic system with different wind power 

penetrations. The study analyzed the adequacy of hydropower to smooth the variability of wind 

power, the effects of combined very large penetration of wind power and hydropower on spot 

prices, and the use of transmission lines and conventional power plants due to increased wind 

power production. The most important limitations arising from chains of stations and reservoirs 

were taken into account. This river system model was used to check the accuracy of dispatch 

from a more coarse market model, which aggregated the hydropower plants into larger groups. 

The database for the hydropower plants and reservoirs enabled a more accurate and detailed 

aggregation of hydropower in the market model.

The Nordic system has an estimated peak load of 74,000 MW (2010 estimate) and gets 60% of 

electricity from hydropower, of which most have large reservoirs. Conventional generation 

capacity was estimated at 93,000 MW in 2010 with 2,360 MW of transmission interconnections. 

The study analyzed wind power energy penetrations of 10%, 20%, and 30%, with the intention 

of determining whether or not there is enough regulation available from the hydropower to deal 

with wind power variation and forecast errors. The model had stochastic wind power 

presentation. Since a significant amount of wind power was added and only little conventional 

capacity was retired, system adequacy was not an issue. The study also examined the effect of a 

large amount of low marginal price production on market prices, including assessment of 

hydropower plants participating in the regulation market.

The study concluded that a large penetration of wind power in a hydro-dominated power system 

will lower the spot price of electricity dramatically, which creates a challenge to get new 

investments in the system. It is unclear whether this kind of system could arise based on the 

markets even if it would be the most cost-effective way to serve load from a system perspective. 

It appears that the regulation capacity of hydropower in the Nordic countries is large enough to 

support at least 30% wind energy penetration.

Because the Nordic system has thousands of hydropower plants and more than a thousand 

reservoirs, it has to be aggregated for a market model in order to keep the model solvable. The 

study aggregated hydropower based on a database of river systems and on analyses of the 

restrictions that river systems and reservoir sizes place on the use of hydropower. Results show 

that a large part of hydropower capacity should be capable of flexible operation.

Relative to these conclusions, the expected results of Wind Task 24 for this study are as follows:
IEA Wind Task 24 Final Report, Vol. 1

84

• The study identified a practical system configuration of 60% of electricity from hydropower, 

most of which being reservoir hydropower, and 30% of electricity from wind power. Because 

old power plants were not retired, there were no problems with system adequacy.

• A large penetration of wind power in a hydro-dominated power system will lower the spot 

price of electricity dramatically, which creates a challenge to get new investments in the 

system. It is unclear whether this kind of system could arise based on the markets even if it 

would be the most cost-effective way to serve load from a system perspective.

4.2.3.4 Norwegian Case Studies

Because the wind resource in Norway is well correlated with the load, and due to the large 

amount of hydropower generation that is present, the Foundation for Scientific and Industrial 

Research at the Norwegian Institute of Technology (SINTEF) investigated the ability to integrate 

wind and hydropower. For the purpose of the Task 24 research, two case studies were 

contributed:

• The first study looked at wind power in areas with limited power transfer capacity and 

subject to grid congestion. The question to be addressed here was to see how much wind 

power could be integrated without deleteriously affecting the hydropower production. 

• The second case study considers the impact of wind power on system adequacy. Considering 

that the region has favorable wind resources, the study was conducted to determine whether 

or not adding wind power to the hydro-based system will be sufficient or if additional 

measures must be taken to secure system adequacy.

The first SINTEF case study considered wind integration into an area of the Nordic system with 

limited power transfer capacity. When planning wind power in areas with limited power transfer 

capacity, conservative assumptions may lead to unnecessarily strict limitations on the possible 

wind installation. By introducing AGC and coordinated power system operation, a large increase 

in installed wind power is viable.

The purpose of this study was to assess grid integration of large wind farms subject to grid 

congestions. Emphasis was put on how different control strategies for handling congestion 

situations affect the operation and economics of the studied regional power system. When 

assessing the impact of wind power on the power system operation, it is necessary to take into 

account the variable and dispersed nature of wind power. This study and previous studies have 

shown that in the Nordic region, the periods with highest wind generation typically appear in the 

winter season when the consumption also is high, which has a positive impact on utilization of 

the existing transmission capacity. Moreover, this study showed that the power smoothing effect 

of geographically dispersed wind farms gives a significant reduction of discarded wind energy in 

constrained networks, compared to a single up-scaled wind farm site.

The specific case study presented consists of a regional power system with assumed 420-MW 

power transfer capacity. With regard to integrating wind energy, the most conservative approach 

allows for only 115 MW of wind power in the constrained network with 420 MW of capacity, as 

this will not require any control actions even in the very unlikely case of maximum wind and 

hydro generation (115 MW + 380 MW) at the same hour as the historically lowest consumption 

(75 MW). However, the viable amount of wind power that can be installed is expected to be 

much higher, not only because of the smoothing effect of geographically dispersed wind farms, 
IEA Wind Task 24 Final Report, Vol. 1

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but also because the periods with highest wind generation typically occur in winter, when the 

consumption also is at its highest. Since the hydro inflow occurs mostly during summer, this 

wind characteristic is beneficial for the system operation.

An hourly simulation model of the regional power system was implemented in MATLAB using

a 30-year time series of wind output, electricity consumption, hydro flow and generation, and 

electricity market prices. The Multi-Area Power Market Simulator (EMPS) model, a commercial 

model developed at SINTEF Energy Research in Norway for hydro scheduling and market price 

forecasting, was employed to generate several of these time series. EMPS is a complex, 

stochastic optimization model that simulates the optimal operation of hydropower resources in a 

region with a stochastic representation of inflow to the hydropower stations and a number of 

physical constraints taken into account.

The results of the study show that for the specific system studied, up to 600 MW of wind power 

is possible—without noticeable reduction in income from energy sales compared to an ideal noncongested case—by applying coordinated operation of the wind power and hydropower plants. 

These results are achieved for a hydropower system with a relatively small reservoir and a high 

share of non-storable water inflow (37% of the total storable plus non-storable inflow). Even if 

the local hydropower plant follows the generation schedule unaffected by wind power, the 

reduction in income due to discarded wind energy is as low as 1% to 5%, depending on the 

annual wind speed and water inflow. Power system coordination allows for surprisingly large 

amounts of wind power. It is essential to account for power system flexibility and the variable

and dispersed nature of wind power. The methodology presented facilitates this and represents a 

rational approach for power system integration of wind farms in areas with limited transfer 

capacity.

The second SINTEF case study analyzed a regional, hydro-based power system with weak 

interconnections. This case study considered the impact of wind power on system adequacy. The 

impact was assessed using data from a real-life, regional, hydro-based power system, although 

data was simplified and fitted for the purpose of the work. The region has a predicted need for 

new generation and/or reinforcement of interconnections to meet future demand. Considering 

that the region has favorable wind resources, the study was conducted to determine whether or 

not adding wind power to the hydro-based system will be sufficient or if additional measures 

must be taken to secure system adequacy.

System adequacy relates to the ability of the system to meet the load demand. In this study, this 

was addressed considering (1) the system’s ability to supply the annual load and (2) the system’s 

ability to meet the peak demand. The system’s ability to supply the annual load was assessed 

using 30 years of recorded data of hydro inflow and wind speed. The system operation was

simulated to quantify annual energy balance within the region, including hydro, wind, and 

import/export through interconnections with neighboring regions. 

The system ability to meet the peak demand was assessed by calculating the loss of load 

probability for the system, using standard statistical techniques (see Section 5.3.3 of Volume 2 

for more details). The calculation takes account for the installed generation and transmission 

capacity, the probability of outages, and the probability of wind power generation at the hour of 

peak demand. 
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Three cases have been considered: the installed wind power is 62 MW (Case B) and 1,062 MW 

(Case A and Case C), which correspond to 186 GWh and 3,186 GWh of annual generation. With 

a 3,780-MW peak load, the wind power penetration becomes 1.6% (Case B) and 28.1% (Case A 

and Case C). The annual load is 21,024 GWh, which gives wind energy penetration levels of 

0.9% (Case B) and 15.2% (Case A and Case C).

The study concluded that wind power will have a positive effect on system adequacy in a 

regional hydro-based power system. Wind power contributes to reducing the loss of load 

probability and improving the energy balance. Adding 3 TWh of wind or 3 TWh of gas 

generation are found to contribute equally to the energy balance, both on a weekly and annual 

basis. Both wind and gas improves the power balance. The capacity value of gas is found to be 

about 95% of rated, and the capacity value of wind about 30% at low-wind energy penetration 

and about 14% at higher wind penetration. The smoothing effect due to geographical distribution 

of wind power has a significant impact on the wind capacity value at high penetration. Indeed, 

similar results have been reported from various national studies (see Figure 40). The significance 

of this study is therefore related to the real-life case studied, being a region rather than a national 

system, and demonstrating the relevance of applying system adequacy studies for generation 

expansion and transmission planning of regional systems.

4.2.3.5 Swedish Case Studies

Below two Swedish studies will be presented. The first one is a detailed study of one river, 

where the aim was to simulate how the hydropower along this river can balance wind power, and 

the second study analyzed how the rivers in the North part of Sweden can balance wind power in 

the same region. Both studies were conducted by the KTH, the Swedish Institute of Technology.

The first Swedish case study analyzed the possibility of balancing wind power with hydropower 

plants located along one certain river. The aim of the simulation is to study whether an increased 

amount of wind power might decrease the efficiency of the hydropower system along an 

interconnected river system. The study method used was to (1) plan the hydropower system for a 

week (deterministic approach); (2) simulate changes in wind power production and load during 

the coming hour; (3) estimate how the power system was operated since it was not according to 

plan; (4) re-plan the rest of the week; and (5) go back to step 2 until all hours during the week 

have been simulated. This means that forecast uncertainties concerning both wind power and 

load were considered, and the hydropower system operation was optimized and re-optimized 

when new information was available. The model was constrained in that it was assumed that a 

certain amount of wind power was balanced using hydropower resources in a certain river.

The hydropower system studied consisted of seven hydropower stations with a total capacity of

478 MW, each modeled with installed capacity, varying efficiency (marginal production 

equivalents) depending on discharge, reservoir capacity for each station and delay time between 

the different hydropower stations. Wind power penetration was studied for three different 

scenarios; 30, 60, and 90 MW. The result was then extrapolated in order to draw conclusions for 

wind power integration in the whole of Sweden. The amount of wind power studied in the 

certain hydropower system corresponded to a penetration in whole Sweden should equal to 6.5–

7.5 TWh/year (i.e., 5 % of total energy production per year). In the extrapolated case, the 

balancing is assumed to be performed in the whole of Sweden.
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The results from the simulations indicate that Swedish wind power installations that generate 

about 2–2.5 TWh/year do not affect the efficiency of the Swedish hydro system. At wind power 

levels of about 4–5 TWh/year, it is estimated that the amount of installed wind power should be 

increased by about 1% to compensate for the decreased efficiency in the hydro system. At wind 

power levels of about 6.5–7.5 TWh/year, the additional wind power needed to compensate for 

loss of hydro efficiency is about 1.2%, but this figure has to be verified with more extended 

simulations.

The aim of the simulation in the second Swedish case study was to study the possibility of 

balancing wind power in northern Sweden using hydropower in northern Sweden. For each week 

studied (12 different weeks per year were studied) and wind power level, the method used was 

to: (1) set up a certain wind power scenario; (2) define a goal for each reservoir level at the end 

of the studied week including a range of flexibility for this level; and (3) perform a deterministic 

optimization (linear programming approach) for how to use the available water as efficiently as 

possible (maximize the production) for the studied week, considering: wind power production, 

hydrological constraints including juridical restrictions, export capability, local load, and thermal 

production. Hourly load and wind profiles employed were drawn from the same week and year, 

whereas the hydro time series was from a typical water year.

The wind power hourly data were simulated wind power series from 19 sites in northern Sweden. 

Available data were from 1992–2001. The total wind power production was obtained by just 

summing up the data from the 19 sites since no transmission constraints within the studied area 

were considered. The simulated series had a total installed capacity of 795 MW and the output 

was scaled to 1,000; 4,000; 8,000; and 12,000 MW. All hydropower stations larger than 10 MW 

in the studied area were considered (i.e., 154 hydropower plants with a combined capacity of 

13.2 GW), which corresponds to about 80% of the installed capacity of all hydropower in 

Sweden. These stations were modeled with a variable efficiency at peak production as well as at 

lower levels (piece-wise linear marginal production curve). Reservoir volumes and constraints, 

juridical restriction concerning e.g., minimum flow, and delay times between different stations 

were also considered. Inflows from 2007 (a rather “normal” inflow year) were applied. Twelve 

different simulations were performed for different inflows, and reservoir start and end limits.

However, it has not been possible within this project to develop sufficiently detailed models of 

season and short-term planning. Also, the modeling of the electricity market is quite simplified. 

All in all, this results in a model showing which technical possibilities there are to balance wind 

power variations by hydropower, but more research is required to study how much of this 

balancing capability will be made available to the electricity market under different regulatory 

frameworks.

The conclusion of the study was that the existing hydropower in northern Sweden has sufficient 

installed capacity and is fast enough to balance even large amounts of wind power. The 

challenge for a large-scale expansion of wind power is to find an outlet for all electricity 

generation. Improved planning tools can sole this challenge, but it could also be profitable to 

make investments in, for example, reinforced export capacity. The model predicted spill to 

occur, but to an overwhelming extent, such a spill can be avoided by using efficient tools for 

season planning. Only in a few cases—and then, in particular, for a wind power expansion of 

12,000 MW—will there be a spill that depends on insufficient balancing capability in the 

hydropower.
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4.2.3.6 United States Case Studies

The case studies contributed by the United States originate from three different river systems and 

electrical balancing areas, as listed below:

• Missouri River and the Western Area Power Administration

• Upper American River and the Sacramento PUD

• Columbia River and the Grant County PUD

In these studies, each system differs in its basic characteristics related to wind integration: 

organizations involved and balancing area setup and generation resources, hydro system 

characteristics, purpose of study, and constraining factors. However, each of these studies did 

seek to determine the basic impacts of wind integration in terms of the ancillary services required 

to handle the additional variability and uncertainty that wind power introduces into the balancing 

area net load. The third study also investigated the impact of wind integration on system flow 

constraints.

The first U.S. case study analyzed wind integration into the balancing area operated by WAPA

and supplied by hydropower facilities located along the Missouri River. This study considered 

integrating five levels of wind power (80 MW; 100 MW; 250 MW; 500 MW; and 1,000 MW) 

into the WAPA control area with its peak load of 2,700 MW. Thus, the wind penetration level 

(defined by wind power capacity divided by peak load) for these cases was 3%, 3.7%, 9.3%, 

18.6%, and 37% respectively. The load is currently served by a combination of hydropower 

plants along the Missouri River system and thermal power plants (coal-fired steam). The 

hydropower capacity is 2,400 MW from six hydro facilities containing multiple years of water 

storage.

The most challenging aspect of this study was its organizational complexity. This study was 

conducted by EnerNex Corporation and Wind on the Wires for NREL, in cooperation with 

WAPA and USACE. The six hydropower facilities located at the dams within WAPA’s Upper 

Great Plains Region, are run by USACE managed within its North-Western Division as governed 

by written guidelines in the Missouri River Master Manual (www.nwdmr.usace.army.mil/mmanual/mast-man.htm). USACE updates this manual each year; provides 

guidance to the operators at each dam concerning water releases; and incorporates recent and 

projected hydrological conditions, environmental requirements (e.g., accounting for bird and fish 

survival), desired lake levels, etc. The dams are all located on the main stem of the Missouri 

River in the Northern-Midwest United States. This type of organizational complexity is not 

uncommon for hydropower systems in the United States, and this represents a real challenge for 

wind and hydropower integration where this is the situation.

The purpose of this study was to perform a statistical analysis to determine the impacts of the

wind integration on the system regulation (10-minute variations), load following (hour-to-hour), 

magnitude of ramping during the morning and evening load ramps, and the effect of wind 

forecast errors on the aggregate hour-ahead and day-ahead forecast error of load net wind versus 

load alone. Results of the study led to the following conclusions:

• The amount of “10-minute regulation” capacity that would be required to compensate for the 

additional fluctuations wind power adds to the system due to variations of the 10-minute net 
IEA Wind Task 24 Final Report, Vol. 1

89

load signal relative to the 2-hour tendency was found to be minimal (≤ 1 MW) for wind 

penetration levels up to 250 MW (9.3% wind penetration), noticeable (≤ 6.5 MW) at 

500 MW (18.6% wind penetration), and substantial (≤ 21.5 MW) at 1,000 MW (37% wind 

penetration). For the purpose of this study, the “10-minute regulation” is additional 

generation needed to handle the increase in fluctuations of the net load caused by wind power 

variations. 

• The load following trend—computed via changes in hourly load and compared to changes in 

hourly load net wind—showed a similar result to the regulation in that the influence of the 

wind power did not become significant until 500 MW of wind was absorbed into the system.

• Of importance in any electrical system is the ability of the system operator to use available 

generation resources to effectively and economically meet the morning and evening ramping 

requirements. The statistical study demonstrated that the load changes during the morning 

and evening ramping periods were very similar for the load alone and the load net wind, even 

up to 500 MW of wind power (18.6% penetration). After this level, the wind does impact the 

ramping requirements, increasing the number of larger ramps that occur and increasing the 

maximum level of ramping needed during the year.

• In investigating the effect of wind forecast errors, the error in the wind forecast was 

combined with load forecast errors and then compared to the load forecast errors alone. Due 

to the existing load forecast errors in the WAPA system, there is little noticeable impact of 

wind generation on the day-ahead, hour-by-hour forecast until the penetration reaches 

500 MW. 

In conclusion, the statistical study presented has indicated that in the WAPA system, significant 

operational impacts from wind energy—those that must be dealt with in planning and

operation—will likely arise when the wind penetration approaches 500 MW (about 18% of the 

peak system load). Below 10% wind penetration, the impacts on 10-minute regulation, load 

following, morning and evening ramping, and the load net wind forecast error are somewhat 

modest.

The second U.S. case study focused on hydropower resources along the upper American River 

and operated by the Sacramento Municipal Utility District. The study focused on the impacts that

four proposed penetration levels of wind generation would have on regulation requirements, 

equivalent capacity values, and integration costs. The primary objective was to assess the 

stochastic nature of the power produced from additional wind power plants and the impacts they 

have on the need for additional fast-ramping regulation and load following reserves in the 

Sacramento Municipal Utility District balancing area. Also investigated was the ability to 

provide “regulation” from the hypothetical Iowa Hill pumped storage facility.

Hourly simulation cases were completed for at least one full year of data for four proposed wind 

generation penetration levels. Wind generation data for the all cases was synthesized from the 

WindLogics Mesoscale Model Version 5 meteorological simulation data for the historical year 

2003. Integration cost in this study is defined as the difference between the actual production 

cost incurred to serve the net of actual load and actual wind generation and production cost from 

the reference case, where wind is perfectly known and adds no variability to the control area, and 

where next-day load is the only uncertainty.
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The study investigated the affect on the Sacramento Municipal Utility District’s control area of 

the following four levels of wind generation: 102 MW (Case 1), 250 MW (Case 2), 450 MW

(Case 3), and 850 MW (Case 4). These correspond to the following wind penetration levels, 

computed by dividing the wind capacity by peak system load: 2.7%, 6.7%, 12.1%, and 22.8%, 

respectively. Specifically, the project sought to investigate the effect on the fast regulation 

requirement and integration costs of wind energy for the different cases. The study found lower 

penetrations of wind generation have only a small impact on fast regulation requirements, but 

begin to dominate as the penetration increases. The results show a very substantial reduction in 

operating cost and integration costs with the hypothetical Iowa Hill pumped-storage facility 

operating (as much as $5/MWh). Furthermore, the results also show that integration costs 

decrease with increasing diversity of wind generation assets. Integration cost in this study was 

defined as the difference between the actual production cost incurred to serve the net of actual 

load and actual wind generation and the production cost from the reference case, where wind is 

perfectly known and adds no variability to the control area, and where next-day load is the only 

uncertainty. A summary of the integration costs are provided in Figure 42, where the four cases 

correspond to the four penetration levels mentioned above. For each case, five different scenarios 

of how to handle the enhanced variability and uncertainty of net load due to wind power were 

considered.

Summary of Integration Cost by Case (Wind Penetration Level)

-2.00

0.00

2.00

4.00

6.00

8.00

10.00

Case 1 Case 2 Case 3 Case 4

Integration Cost ($/MWh)

Base

Base Discounted Forecast

Base PIRP w / Discounted Forecast

Iow a Hill Base

Iow a Hill JIT Commit

Figure 42. Wind integration costs for four wind integration penetration levels: Case 1 with 102 MW, 

Case 2 with 250 MW; Case 3 with 450 MW, and Case 4 with 850 MW; these correspond to wind 

penetration levels as a percent of peak system load of 2.7%, 6.7%, 12.1%, and 22.8%; tor each 

case, five different strategies for providing system balancing were considered 

(Source: Zavadil 2008)

The authors determined that the integration cost drops significantly with the wind penetration 

level. At first, this seems counterintuitive since it would seem likely that more wind would 

require less efficient commitment to handle the uncertainty and variability in the wind energy 

delivery. One aspect of lowering the effect of higher wind penetrations is increased geographic 
IEA Wind Task 24 Final Report, Vol. 1

91

diversity. Cases 1 and 2 are concentrated scenarios with all of the turbines in a relatively small 

area, and are affected by essentially the same meteorology at the same time. In Cases 3 and 4, the 

wind plants are scattered over a much greater geographic area. This tends to smooth the wind 

because while one site may have low wind, another may have high wind.

The modeling conducted showed that unit commitment and dispatch become difficult at 

penetration levels of 850 MW without the Hour Ahead Scheduling Process (HASP), yet work

very well at the 450-MW level. Although the cases that include involvement in the Participating 

Intermittent Resources Program will require fewer reserves to be provided by the Sacramento 

Municipal Utility District, there are only very small decreases in the integration costs that result

from these cases. Changes in the Hour Ahead Scheduling Process market structure could 

significantly affect integration costs. A more detailed treatment of error analysis will yield more 

accurate results. Wind forecasting error, load forecasting error, and any relation between the two 

should be studied.

The third U.S. case study considered two hydropower plants located along the Columbia River 

and operated by the Grant County PUD No. 2. Grant PUD was interested in studying ways to 

expand its wind energy generation through effective integration with its two-dam Priest Rapids 

Project on the Columbia River in central Washington. In addition to its 900 MW of hydropower,

Grant PUD purchases a share of the 63.7 MW Nine Canyon Wind Project.

The two primary goals of the study were: (1) to understand the impacts of Grant PUD’s current 

efforts at integrating wind and hydropower, and (2) to study the potential for future expansion of 

wind integration. In addressing these goals, the Grant PUD sought to understand the impacts of 

wind integration on its hydro operations, including effects on spill; approximating an economic 

value for the wind energy; and, most importantly, identifying the frequency and magnitude of 

surpassing generation limitation or dropping below the minimum flow requirement (for fish 

survival).

Study results focus on three primary interest areas: (1) wind power effects in the regulation and 

load following time frames; (2) impacts associated with system planning in the unit commitment 

time frame; and (3) understanding the impacts on exceeding system constraints related to 

maximum generation (i.e., keeping sufficient reserves) or minimum flow levels to comply with 

environmental regulations for fish survival. The penetration levels of wind power penetration 

considered in the project were 12 MW (1.8%), 63.7 MW (7.8%), and 150 MW (18.6%), 

computed as a percentage of peak load (including sales of energy). 

Study results for the 2006 data year suggest that the overall impact on system statistics for 

regulation and load following is quite modest, even at a wind energy penetration of 150 MW 

(~19% wind penetration by capacity). The small statistical impact suggests that, absent other 

constraints, the physical generation resources are sufficient to handle wind variability at this 

level. However, due to changes in the distribution of load following hourly changes, there are 

some potentially significant operational challenges in scheduling the resources without infringing 

upon system constraints. To assess the impact on system constraints, a pre-schedule (i.e., dayahead) planning simulation was devised and conducted, using an hourly time resolution. Figure 

43 shows the effect of day-ahead wind power forecast errors on the low-load hour minimum 
IEA Wind Task 24 Final Report, Vol. 1

92

capacity “exceedences”18 (dropping below the minimum capacity, and therefore dipping below 

the minimum flow permitted). With respect to this limit, the effect is not pronounced as the blue 

columns shown (representing the number of flow exceedences if incorporating 63.7 MW of wind 

power and using a day-ahead forecast only) are nearly the same height as the red columns 

corresponding to the system as run (with 12 MW of wind power), with an increase only in the 

short-duration violations. Note that no attempt was been made in this analysis to see if the 

increased exceedences could be averted by real-time or “hour-ahead” transactions. Rather, the 

intent was to assess the impact on the number of exceedences under a reasonable planning 

algorithm. These results do show that an increased number of exceedences occur, but that the 

increase is only modest. It is also possible that many of these instances could be handled during 

the day of operation, and at some cost. Addressing this latter point would be the next logical step 

for Grant PUD in continuing this analysis.

Figure 43. Number of exceedences (dropping below) the minimum allowable capacity due to a 

flow constraint, for the system as run and with 63.7 MW of wind planned into the system in the

day-ahead pre-schedule (Source: Acker 2007)

4.2.4 Practical System Configuration

Figure 44 provides a conceptual view of a practical configuration for combining wind and 

hydropower in a BA. The key take away from this illustration is that wind and hydropower are 

system resources that help serve the load via the transmission grid, and that they are each 

controlled by the TSO. Addressing the incremental impacts of wind integration is done in the 

context of the entire system, with all of its load and generation resources, and not in isolation 

 18 An “exceedence” refers to either one of the following: (1) the hydropower generation level rising above the 

permitted level for reliability (and thus dipping into the contingency reserves in order to meet the net load) or (2) the 

generation level being reduced to a level where the flow exiting the second of the two Grant PUD hydro facilities 

falls below the level required for fish protection downstream of the plant.
IEA Wind Task 24 Final Report, Vol. 1

93

from them.19 It is possible that due to transmission limitations the resources of the entire 

balancing area will not be available to correct imbalances that arise in transmission constrained 

area within the BA. In such a case, the configuration proposed remains the same, with the 

exception that the BA shown becomes the transmission constrained area and responses to 

imbalances must utilize resources available within the area or those that can be delivered through 

the transmission constraint.

Balancing Area

System Operator / TSO

Thermal

Generation

Loads

Transmission/Distribution Power to grid

Transmission 

Interconnections

Power to grid

Power from grid

Power to grid Power to grid Wind 

Power Hydro

Power

Figure 44. A practical configuration for wind and hydropower integration (note the red dashed 

lines in the figure refer to information flow including generation control signals) (Source: T. Acker 

presentation, Task 24 R&D Meeting #5, Québec City, Québec, Canada, June 2008)

 19 The obligation of a system operator is to balance net load with generation while honoring transmission constraints. 

Because variations in wind power production are generally uncorrelated with variations in load (as described in 

Chapter 2), it is not necessary to balance the variations of any single wind power plant, or any single load, but rather 

the aggregate of all loads net wind. This results in a lower overall requirement for balancing actions, and more 

effective use of available resources. Thus, no attempt is made to balance the output of one wind power plant using 

the resources of one hydro plant to produce a flat output.
IEA Wind Task 24 Final Report, Vol. 1

94

5 Conclusions

Chapter 1 of this report introduced the aspects of electric system operation and planning that are 

of most relevance to wind integration: utilities and markets, ancillary services, and system 

planning and operation. It provided the vital background necessary to understand the reasons for 

forming Task 24, determine the objectives and questions being addressed, and present the 

members and work plan of the task. Chapters 2 and 3 went on to provide descriptions of wind 

power and hydropower, respectively, discussing the aspects of importance to the Task 24 

objectives and expected results. Chapter 2 presented a perspective on the value of wind energy, 

then went on to describe in detail the characteristics of wind power variability and uncertainty, 

its contribution to system capacity, and their relationship to power system operation and 

planning. Chapter 3 provided an overview of hydropower, and then discussed in detail aspects of 

hydro system operation and planning of relevance to electrical system operation and planning. Of 

particular importance were aspects of hydropower of importance to wind integration. This 

chapter concluded with a summary of issues related to hydropower as a balancing resource and 

for energy storage. Next, Chapter 4 described power system operation and balancing in systems 

with wind power and hydropower, drawing upon the case studies and other relevant literature. 

The results of the participant case studies, in particular, were described in detail in this chapter 

with reference back to the questions posed when Task 24 was formed. It is the purpose of this 

chapter to summarize and present the conclusions of the task and suggested future directions for 

the study.20

At the end of Section 1.2, a set of questions were presented that motivated the formation Task 24 

and led to the objectives and expected outcomes of the task. These questions are repeated below 

because they create a convenient framework for summarizing the conclusions:

• Grid Integration Impacts and Costs: What is the impact of wind power on the power system 

balancing area, and specifically, the ancillary services/reserves required; long-term system 

planning (capacity value); and transmission system (e.g., scheduling bottlenecks, etc.)? What 

are the appropriate study methods?

• Hydropower Impacts: What impact will provision of these ancillary services have on the 

hydropower system? Impacts include those on the physical resources (e.g., operations and 

maintenance); operational flexibility; and hydro system priorities (e.g., meeting flow 

constraints, satisfying environmental regulations).

• Economics: What is the overall economic value of wind energy in the hydro system? What 

“opportunity costs” are incurred for the hydro system in providing ancillary services to wind 

power (thus not being available for scheduling), and what are the economic 

benefits/opportunities in doing so? What is the effect of market configurations and system 

operation (e.g., scheduling intervals)? Are there wind/hydro “products” that can be of value 

both to power customers and hydropower providers (e.g., energy storage and redelivery)?

• System Configuration: Based upon the answers to the questions above, what are practical 

configurations for integrating wind and hydropower?

 20 At the final R&D meeting of Task 24, participants decided not to extend the task, but rather to continue 

addressing the questions posed in forming the task and furthering the analyses conducted in the case studies through 

participation in IEA Wind Task 25.
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95

A summary of conclusions drawn related to each of these topics are provided below.

5.1 Grid Integration Impacts and Costs

Data presented in Chapter 2 provided a sense for the order of magnitude and frequency of power 

output changes with which a system operator or planner must deal. The data suggested that there 

will be a relatively small impact at the regulation (minute-to-minute) time scale, but becoming 

considerable at the hourly time scale and beyond (e.g., load following, unit commitment, reserve 

requirements), especially at high levels of wind penetration. In addition to being variable, wind 

power is also uncertain, and though accurately predictable much of the time, can suffer from 

large forecast errors that may occur at inopportune times during system operation. Wind power, 

while primarily an energy resource, does have a capacity value that should be considered in 

system planning. What makes wind power different to a system operator and planner as 

compared to other power resources is its variability and uncertainty, and learning how to 

understand and work with these characteristics. The overall impact of the wind power variations, 

forecast errors, and their associated integration cost—combined with the cost of wind energy, its 

marginal value, and the positive benefits it brings to the electrical system—depend on a host of 

factors including the system load, the generation fleet, operational and market flexibility, etc., 

and can only be accurately estimated via a thorough simulation of the power system. Several 

case studies of this task addressed wind integration impacts and costs, the relevant conclusions of 

which are summarized below.

• Finnish Case Study #1

•

: This study showed that even with the limited flexibility of 

hydropower (run-of-the-river with small reservoirs), a large part of wind power forecast 

errors can be provided for by shifting hydropower back and forth inside 1 day. The study also 

showed that when correcting the forecast errors of wind power at a large balancing market in 

which hydropower produces most of the balancing (like in Nordic countries), there is not a 

great benefit of combining/integrating wind power and hydropower at a single producer. It is 

more cost effective to bid all flexibility of hydropower to the balancing market and use it 

from there to correct the system imbalances than to use it for dedicated balancing of wind 

power.

Finnish Case Study #2:

•

The study analyzed wind power energy penetrations of 10%, 20%, 

and 30% in the Nordic system (74,000-MW peak load), with the intention of determining 

whether or not there is enough regulation available from the hydropower to deal with wind 

power variation and forecast errors. The study identified a practical system configuration of 

60% of electricity from hydropower, most of which being reservoir hydropower, and 30% of 

electricity from wind power. Results showed that a large part of hydropower capacity should 

be capable of flexible operation and able to provide the additional regulation required due to 

the high penetration of wind power.

Norwegian Case Study #1: This case study presented a regional power system with an 

assumed 420-MW power transfer capacity. With regard to integrating wind energy, the most 

conservative approach allows for only 115 MW of wind power in the constrained network 

with 420 MW of capacity, as this will not require any control actions even in the very 

unlikely case of maximum wind and hydro generation (115 MW + 380 MW) at the same 

hour as the historically lowest consumption (75 MW). The results of the study showed that 

for the specific system under consideration, up to 600 MW of wind power is possible—

without noticeable reduction in income from energy sales compared to an ideal non-
IEA Wind Task 24 Final Report, Vol. 1

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congested case—by applying coordinated operation of the wind power and hydropower 

plants. 

• Norwegian Case Study #2

•

: This case study considered the impact of wind power on system 

adequacy, assessed using data from a real-life, regional, hydro-based power system. Three 

cases were considered: the installed wind power is 62 MW (Case B) and 1,062 MW (Case A 

and Case C), which correspond to wind power penetration levels of 1.6% (Case B) and 

28.1% (Case A and Case C). The annual load is 21,024 GWh, which gives wind energy 

penetration levels of 0.9% (Case B) and 15.2% (Case A and Case C). The study concluded 

that wind power will have a positive effect on system adequacy in a regional hydro-based 

power system. Wind power contributes to reducing the loss of load probability and 

improving the energy balance. Adding 3 TWh of wind or 3 TWh of gas generation are found 

to contribute equally to the energy balance, both on a weekly and annual basis. Both wind 

and gas improves the power balance. The capacity value of gas is found to be about 95% of 

rated, and the capacity value of wind about 30% at low-wind energy penetration and about 

14% at higher wind penetration.

Swedish Case Study #2

•

: The aim of the simulation in the second Swedish case study was to 

study the possibility of balancing wind power in northern Sweden using hydropower in 

northern Sweden. The simulation included a total installed capacity of 795 MW of wind 

power, and that output was scaled to 1,000; 4,000; 8,000; and 12,000 MW. All hydropower

stations larger than 10 MW in the studied area were considered (i.e., 154 hydropower plants 

with a combined capacity of 13.2 GW, which corresponds to about 80% of the installed 

capacity of all hydropower in Sweden). The conclusion of the study was that the existing 

hydropower in northern Sweden has sufficient installed capacity and is fast enough to 

balance even large amounts of wind power. The model predicted spill to occur, but that to an 

overwhelming extent such a spill can be avoided by using efficient tools for especially the 

season planning. Only in a few cases—and then, in particular, for a wind power expansion of 

12,000 MW—will there be spill that depends on insufficient balancing capability in the 

hydropower.

U.S. Case Study on the Missouri River

•

: The case study on the Missouri River analyzed wind 

integration into the balancing area operated by WAPA and supplied by hydropower facilities 

located along the Missouri River. This study considered integrating five levels of wind power 

penetration of 3%, 3.7%, 9.3%, 18.6%, and 37%. The hydropower capacity is 2,400 MW 

from six hydro facilities containing multiple years of water storage, and the peak system load 

was 2,700 MW. The statistical study concluded that in the WAPA system, significant 

operational impacts from wind energy—those that must be dealt with in planning and 

operation (regulation, load following, system ramping of net load)—will likely arise when 

the wind penetration approaches 500 MW (about 18% of the peak system load). 

U.S. Case Study Sacramento Municipal Utility District: This case study focused on 

hydropower resources along the upper American River and operated by the Sacramento 

Municipal Utility District. Hourly simulation cases were completed for at least one full year 

of data for four proposed wind generation penetration levels: 102 MW, 250 MW, 450 MW, 

and 850 MW. These correspond to the following wind penetration levels (computed by 

dividing wind capacity by system peak load): 2.7%, 6.7%, 12.1%, and 22.8%, respectively. 

The study found lower penetrations of wind generation have only a small impact on fast 
IEA Wind Task 24 Final Report, Vol. 1

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regulation requirements, but begin to dominate as the penetration increases. Wind integration 

costs were computed to range from about $2–8 USD/MWh of wind energy produced. The 

results show a very substantial reduction in operating cost and integration costs with the 

hypothetical Iowa Hill pumped-storage facility operating (as much as $5 USD/MWh). 

Furthermore, the results also show that integration costs decrease with increasing diversity of 

wind generation assets.

5.2 Hydropower Impacts

The material presented in Chapter 3 described the salient aspects of hydropower generation 

relevant to wind and hydropower generation. The type and magnitude of ancillary services and 

reserves that can be provided by a hydropower plant depends on whether it possesses significant 

storage or if it is a run-of-the-river plant with limited storage. The flexibility of operation also 

depends on whether or not the hydropower is part of a cascade of dams on a river system, and the 

level of coordination between those on the same river. Hydro facilities often have numerous 

functions—power generation being one—that guide their operation and define their flexibility. 

Layered on top of the physical and functional planning, there may be numerous organizations 

and stakeholders involved, along with differing market or economic situations. It is the 

interaction of the many functions, system configurations, and stakeholders that establish the 

authority, priority, and economics that govern the potential for wind and hydro integration. 

The overarching question for studying wind and hydropower integration is whether systemoperating impacts due to wind power can be accommodated by hydropower within the

constraints on hydropower currently in place (or not easily changed), and in an economically 

advantageous way. And if so, what changes will this cause to hydropower operations or costs? In 

concept, hydropower should be able to provide short- to medium-term buffering of the enhanced 

variability and uncertainty wind power induces in the overall load net wind. Adding wind power 

to the system may or may not help hydropower meet power and other system demands, and the 

influence on other hydro functions, such as water deliveries, must be considered. That said, even 

within the constraints currently imposed on hydropower, it is a valuable system balancing 

resource, and possesses the inherent qualities needed to facilitate wind integration. Five of the 

case studies of this task addressed hydropower impacts, the relevant conclusions of which are

summarized below.

• Australian Case Studies #1 and #3

•

: Hydro Tasmania’s system was modeled with 1,850 MW 

of peak load; a 900-MW minimum load; 2,267 MW of hydropower; and 630-MW/480-MW 

export/import capability via an HVDC interconnect with the Australian mainland. The 

studies found that a high level of wind power can be integrated into the Tasmanian system, 

up to 1,300 MW, if the interconnect with the Australian mainland is used and if measures are 

taken to address low system inertia. The study also identified that commitment of additional 

hydro generators operating in either synchronous condenser mode or tail water depression

mode can largely improve the integration of the wind generation in Tasmania and problems 

associated with low system inertia.

Australian Case Study #2: With respect to reservoir storage, in the case of islanded operation 

of a Tasmanian power system, system storage is unable to effectively absorb all output from 

large-scale wind generation due to coincident of high winds and high inflows. There is an 

increasing negative impact on water storage as wind generation capacity is increased. 

Interconnecting to the Australian mainland, via the addition of the high capacity HVDC 
IEA Wind Task 24 Final Report, Vol. 1

98

interconnection, significantly increases the ability to integrate wind generation in Tasmania 

without a negative effect on the energy in storage. 

• Swedish Case Study #1

•

: The first Swedish case study analyzed the possibility of balancing 

wind power with hydropower plants located along one certain river. The amount of wind 

power studied extrapolated to a penetration in Sweden equal to 6.5–7.5 TWh/year, or 5% of 

total energy production per year. The results from the simulations indicate that Swedish wind 

power installations that generate about 2–2.5 TWh/year do not affect the efficiency of the 

Swedish hydro system. At wind power levels of about 4–5 TWh/year, it is estimated that the 

amount of installed wind power should be increased by about 1% to compensate for the 

decreased efficiency in the hydro system. At wind power levels of about 6.5–7.5 TWh/year,

the additional wind power needed to compensate for loss of hydro efficiency is about 1.2 %, 

but this figure has to be verified with more extended simulations.

U.S. Case Study Grant County PUD

5.3 Economics

: This case study considered two hydropower plants 

located along the Columbia River and operated by the Grant County PUD No. 2. The levels 

of wind penetration considered were 12 MW (1.8%), 63.7 MW (7.8%), and 150 MW 

(18.6%), with each percentage computed as a percentage of peak load (including sales of 

energy). Study results for the 2006 data year suggest that the overall impact on system 

statistics for regulation and load following is quite modest, even at a wind energy penetration 

of 150 MW (~19% wind penetration by capacity). The small statistical impact suggests that, 

absent other constraints, the physical generation resources are sufficient to handle wind 

variability at this level. However, due to changes in the distribution of load following hourly 

changes, there are some potentially significant operational challenges in scheduling the 

resources without infringing upon system constraints. To address this, an hourly simulation 

was conducted using day-ahead wind power forecasts, revealing that additional instances of 

dipping into contingency reserves occur due to missed wind power forecasts, and that 

additional short-duration excursions below the minimum flow requirements (for fish 

survival) also occur. The increases, however, are only modest and many can likely be 

handled during the day of operation, though at some cost.

The wind integration and hydro system impact studies have demonstrated the technical 

feasibility of integrating wind power and hydropower, even in systems with either transmission 

or hydropower constraints. Beyond the technical feasibility, two case studies investigated 

whether or not integrating wind was practical from an economic point of view, or looked at the 

effect of wind integration on the market. These two studies represent a valuable contribution to 

the task, and are a good start in addressing the overall question of economic feasibility.

• Canadian Case Study

•

: Natural Resources Canada conducted a study for a small public utility 

in the United States along the Columbia River that demonstrated that using wind power to 

address load growth is economically feasible. It was also shown that the hydropower 

resources available to the utility being studied were satisfactory to supply low-cost balancing 

resources. In practice, due to underproduction of the wind power plant, it was found that the 

wind power would not have been economically favorable without Renewable Energy 

Production Incentives. 

Finnish Case Study #2: The study analyzed wind power energy penetrations of 10%, 20%, 

and 30% in the Nordic system (74,000-MW peak load). Because old power plants were not 
IEA Wind Task 24 Final Report, Vol. 1

99

retired in the study, there were no problems with system adequacy. Balancing this amount of 

wind power was shown to be feasible, but it was determined that a large penetration of wind 

power in a hydro-dominated power system will lower the spot price of electricity 

dramatically, which creates a challenge to get new investments in the system. It is unclear 

whether this kind of system could arise based on the markets even if it would be the most 

cost-effective way to serve load from a system perspective.

5.4 System Configuration and General Conclusions

As the breadth of the case studies indicate, integrating wind and hydropower can be quite 

complex. A summary of some key observations and conclusions from the work of the 

participants are provided below:

• Wind and hydropower are system resources that help serve the load via the transmission grid, 

and they are each controlled by the TSO. Addressing the incremental impacts of wind 

integration should be done in the context of the entire system, with all of its load and 

generation resources, and not in isolation from them (i.e., not one wind power plant balanced 

by one hydro plant to produce a flat output). 

• When addressing wind integration, one should consider the holistic impact of wind power on 

the system (e.g., a cost-benefit analysis directed toward the electricity customer and effect on 

transmission system reliability), and not just the enhanced balancing requirements due to 

wind power’s variability and uncertainty (e.g., wind power will enhance balancing 

requirements and incur an “integration” cost; however, at the same time the overall cost of 

electricity to the consumer may decrease due to wind energy displacing higher cost 

generation resources).

• The setup and operation of the transmission system and balancing area authority will have a 

profound impact on the ability to integrate wind power and the integration costs incurred.

TSOs where the timing of transactions (committing units, buying and selling of electricity, 

ancillary services, and reserves) is frequent are more capable of integrating wind power and 

at lower costs. 

• Transmission interconnections are important as they can limit wind and hydropower 

integration due to transmission constraints or congestion, or facilitate integration via power 

exchanges with neighboring systems. Larger balancing areas can more easily integrate wind 

and hydropower.

• Electrical systems can function within liberalized electricity markets, via a vertically 

integrated utility that participates with neighboring systems via bilateral transactions, or some 

combination of the two. Wind integration costs and impacts tend to be reduced in market 

systems, especially those with many market actors and flexible resources.

• The wind/hydro case study results were consistent with other wind integration studies in that 

the presence of an efficient and liquid electricity market has a large positive influence on the 

economics, frequently dominating all other factors. Furthermore, an important factor in 

interpreting the economic consequences of integrating wind and hydro is the perspective 

taken by the study: for the overall benefit of the electric customer vs. a single actor in the 

market (e.g., a utility, a wind developer).
IEA Wind Task 24 Final Report, Vol. 1

100

• In conducting wind integration studies, the modeling assumptions and techniques can have a 

significant influence on the results. Therefore, these should be well-specified and understood 

when interpreting results and comparing different studies. Wind integration studies often 

involve the use of production cost models that simulate hourly operation of the power

system. General production cost models (those not specifically developed for or by a 

hydropower-dominant utility) need improvements in how they model hydropower operation, 

water balances, and constraints, in order to better investigate the nuances of wind and hydro 

integration (e.g., the impact of enhanced system balancing requirements on hydro system 

constraints, or the ability to model the constraints). Virtually all production cost models

require further improvement in how they handle wind power and wind power forecasts.

• At low wind penetration levels (~1%), wind integration impacts and costs are very minor.

These transition to more cost and complexity as penetration levels increase to ~20%. Beyond 

~20%, changes in system operational practices are likely necessary to optimally integrate 

wind and hydropower (e.g., use of advanced wind forecasting models incorporated into 

system planning). Islanded or small power systems with weak interconnections may more 

readily experience the effects of the enhanced variability in net load and increased reserve 

requirements caused by wind integration, including impacts on system inertia, and require 

attention in system planning.

• Non-power constraints on the hydropower system can influence the ability to integrate wind 

and hydropower. Such constraints may include higher priority functions of the hydro facility 

that dictate how water is run through the generators, such as irrigation water deliveries;

environmental regulation (e.g., fish passage); recreation; or flood control. While these nonpower constraints are important, they frequently occur on time scales of system operation 

different than those related to wind/hydro integration. Therefore, they do not tend to be 

prohibitive and often may not significantly influence wind and hydro integration, although at 

times they do reduce hydro system flexibility. Of the Task 24 participants, these constraints 

only played a significant role in hydro systems in the United States.

In summary, while hydropower systems possess special characteristics and operating constraints, 

the inherent flexibility of their generators and the potential for energy storage in their reservoirs 

make them well suited to integrate wind into the power system. From an overall perspective, 

wind integration into systems with hydropower is similar to wind integration into any power 

system: hydro resources are employed to meet net load much as they would be deployed to meet 

load alone. The fundamental difference with hydropower, as compared to other generation 

resources, lies in its flexibility. Hydro generators themselves are agile and quick responding; 

however, the use of hydro can be constrained by many other factors such as institutional 

constraints, resource availability, reservoir limitations, environmental restrictions on flow, etc. 

Therefore, when contemplating integrating wind into systems with hydropower, understanding 

the key factors constraining hydro and how they influence system flexibility is important. As 

demonstrated by the several case studies undertaken as part of this task, even amidst significant 

constraints, systems with hydropower resources are capable of wind integration. The primary 

advantage of hydro in integrating wind is its potential to provide ancillary services at a cost less 

than that of thermal resources. 
IEA Wind Task 24 Final Report, Vol. 1

101

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Conference, Milan, Italy.

Söder, L. and Holttinen, H. (2008). “On methodology for modeling wind power impact on power 

systems,” Int. J. Global Energy Issues, Vol. 29, Nos. 1/2, pp.181-198.

USACE (2006). Missouri River Mainstem Reservoir System, Master Water Control Manual, 

Missouri River Basin, Reservoir Control Center, U. S. Army Corps of Engineers Northwestern 

Division, www.nwd-mr.usace.army.mil/mmanual/mast-man.htm.

US DOE. 2008. “20% Wind Energy by 2030; Increasing Wind Energy’s Contribution to U.S. 

Electricity Supply,” U.S. Department of Energy report DOE/GO-102008-2567.

USGS (2004). USGS Fact Sheet 2004-3062, version 2, U.S. Department of the Interior, 

U.S. Geological Survey, pubs.usgs.gov/fs/2004/3062.

Wan, Y. (2004) “Wind Power Plant Behaviors: Analyses of Long-Term Wind Power Data,” U.S. 

National Renewable Energy Laboratory, NREL/TP-500-36551. 

Wan, Y. (2005) “A Primer on Wind Power for Utility Applications,” U.S. National Renewable 

Energy Laboratory, NREL/TP-500-36230. 

Wan, Y. (2008) “Summary Report of Wind Farm Data,” U.S. National Renewable Energy 

Laboratory, NREL/TP-500-44348.

Westrick, K., Storck, P. and Froese, G. (2003). “Reliance on Renewables – The Synergistic 

Relationship between Wind and Hydropower,” Proceedings of the AWEA Windpower 2003 

Conference, Austin, TX.

Wiser, R. and Bolinger, M., (2009) “2008 Wind Technologies Market Report,” US Department 

of Energy, Energy Efficiency and Renewable 

Energy, www.windpoweringamerica.gov/pdfs/2008_annual_wind_market_report.pdf. 

Zack, J.W. (2009) “Wind Power Production Forecasting: The Basics,” Proceedings of the

UWIG/NREL Workshop on Wind Forecasting Applications to Utility Planning and Operations, 

Phoenix, Arizona, USA

Zavadil, R. M. (2006). Wind Integration Study for Public Service Company of Colorado, 

available on-line 

at www.nrel.gov/wind/systemsintegration/pdfs/colorado_public_service_windintegstudy.pdf.
IEA Wind Task 24 Final Report, Vol. 1

104

Zavadil, Robert (2008). Wind Integration Study for the Sacramento Municipal Utility District, 

California Energy Commission, PIER Renewable Energy Technologies Program. CEC-500-00-

034.
IEA Wind Task 24 Final Report, Vol. 1

105

Appendix A: Bibliography of Reports

This appendix presents an extensive list of reports regarding wind integration. This list includes all reports cited in the body of this 

report plus others that may be of interest. The reports are organized alphabetically by country of origin. (Source: Northern Arizona 

University)

Country/ continent 

(leading author) Topic Reference Link

Belgium Wind Integration

Di Marzio G, Fosso O, Uhlen K, Pálsson M P, Largescale wind power integration - voltage stability limits and 

modal analysis, 15th Power System Computation 

Conference, PSCC 2005, Liege

Belgium

Distributed 

Generation, Wind 

Integration

Luther, M. Grid operation and management with large 

scale wind generation, European Conference on 

Integration of Renewable Energy Sources and 

Distributed Generation in Energy Systems, Brussels 25-

26.9.2001

Canada

Wind Integration, 

Energy Markets

AESO, 2006. Wind Integration Impact Studies. Phase 2: 

Assessing the impacts of increased wind power on AIES 

operations and mitigating measures.

Canada Wind-Hydro

Bélanger, Camille and Gagnon, Luc 2002. Adding Wind 

Energy to Hydropower, Energy Policy, 30, pp. 1279-

1284. 

www.elsevier.com/locate/enpol

Canada

Wind Integration, 

Wind-Hydro

Benitez, Liliana E.; Benitez, Pablo C.; and van Kooten, 

G. Cornelius, 2006. The economics of wind power with 

energy storage, Energy Economics 2007, 

doi:10.1016/j.eneco.2007.01.017. 

www.elsevier.com or 

at www.sciencedirect.com

Canada Wind-Hydro

Denault, M., Dupuis. D., Couture-Cardinal. S., (2009). 

Complementarily of hydro and wind power: Improving the 

risk profile of energy inflows, Energy Policy, 37, pp. 

5376-5384. 

www.sciencedirect.com
IEA Wind Task 24 Final Report, Vol. 1

106

Country/ continent 

(leading author) Topic Reference Link

Canada

Wind Integration, 

Wind-Hydro

Hurdowar, Diana; Lafreniere, Marc; Welt, Francois; 

Bridgeman, Stuart G. 2005; Girling, Bill; Gawne, Kevin; 

and Hunter, Kelly. Studying Short-Term Effects of 

Integrating Wind in a Hydro System: Manitoba Hydro 

Case Study. Proceedings of the Waterpower XIV 

Conference, Austin, TX, July, 2005.

Canada

Wind Integration, 

Power Systems

Kehler, John et al. (AESO) 2005. Incremental Impact on 

System Operations with Increased Wind Power 

Penetration. Phase 1: Final.

Canada Wind-Hydro

Krau, S., Lafrance, G., Saulnier, B., Cohen, J., 2003. 

Integrating the Energy Markets in North America: 

Conditions Helping Large-scale Integration of Wind 

Power. 23rd Annual North America Conference of the 

AMEE/USAEE/IAEE Mexico, Oct. 19-21 2003.

Canada

Wind Integration, 

Power Systems

Lafrance, G, et al. 2002, Assessment of the Impact of 

Wind Power Penetration on the Vermont Electricity Grid, 

Hydro Quebec Institut de Recherche

Canada Wind Integration

Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2008) 

Network constrained wind integration on Vancouver 

Island, Energy Policy, Vol. 36, pgs. 591-602, 2008.

Canada Wind Integration

Maddaloni, J.D., Rowe, A.M., Kooten, G.C., (2009). Wind 

integration into various generation mixtures, Renewable 

Energy, Vol. 34, pp. 807-814, 2009.

Canada

Wind Integration, 

Power Systems

Pourbeik, Pouyan, 2004. Integration of Wind Energy into 

the Alberta Electric System - Stage 1: Voltage Regulation 

Study. Prepared for AESO by Electric Systems 

Consulting.

Canada Wind Integration

Pourbeik, Pouyan, 2004. Integration of Wind Energy into 

the Alberta Electric System - Stage 2 and 3: Planning 

and Interconnection Criteria. Prepared for AESO by 

Electric Systems Consulting.
IEA Wind Task 24 Final Report, Vol. 1

107

Country/ continent 

(leading author) Topic Reference Link

Canada

Wind Integration, 

Energy Markets, 

Wind Power 

Variability

Pourbeik, Pouyan, 2004. Integration of Wind Energy into 

the Alberta Electric System - 4: Operations Impact. 

Prepared for AESO by Electric Systems Consulting.

Canada

Wind Integration, 

Wind Power 

Variability

Wang, Rui and Baker, David 2005. Alberta Wind Power 

Variability Study, Alberta Electric System Operator, 

Calgary Place 2500, 330 – 5th Ave. SW Calgary, AB T2P 

0L4, July. 

www.aeso.ca/files/WindVariabilityFinalRepor

t.pdf

Canada Wind Integration

Maritimes Area Wind Power Integration Study Summary 

Report, 2007, NBSO Wind Project

China Wind-Hydro

Yanfang, F., Yibo, W., Qin, C. Wind-Hydro Hybrid Power 

System Stability Analysis. Xinjiang University

Denmark Wind Forecasts

Danielian, Regis, et al. 2007, Surface-Layer Wind and 

Turbulence Profiling from LIDAR: Theory and 

Measurements. Vestas Wind Systems. 

www.risoe.dk/rispubl/art/2007_86_paper.pdf

Denmark Systems Analysis

Energinet.DK, Recent Energinet.dk Papers (3 & 4 quarter 

2005) on: System Analysis and Model Tools, December 

2005

Denmark Systems Analysis

Energinet.DK, Recent Energinet.dk Publications (4 

quarter 2007, 1 quarter 2008) on: System analysis and 

model tools, March 2008

Denmark Wind Integration

Energinet.dk, 2004. Regulation TF3.2.5 Wind turbines 

connected to grids with voltages above 100kV, Dec 

2004. 

www.energinet.dk/en/servicemenu/Library/Li

brary.htm#

Denmark Wind Integration

Kristoffersen, J.R. The Horns Rev Wind Farm and the 

Operational Experience with the Wind Farm Main 

Controller, Proceedings of Copenhagen Offshore Wind, 

October 2005, Copenhagen, Denmark.

Denmark Wind Integration

Lund, H, 2005. Large-scale integration of wind power into 

different energy systems, ENERGY 30 (13): 2402-2412 

OCT 2005 

www.sciencedirect.com
IEA Wind Task 24 Final Report, Vol. 1

108

Country/ continent 

(leading author) Topic Reference Link

Denmark Wind Integration

Lund, H. Large-scale integration of optimal combinations 

of PV, wind, and wave power into the electricity supply, 

Renewable Energy Vol 21(4), pp 503-515, April 2006

www.elsevier.com/wps/find/journaldescription

.cws_home/969/description

Denmark

Wind Integration, 

Energy Markets

Lund, H. and Münster, E., 2006. Integrated energy 

systems and local energy markets, Energy Policy, 

Volume 34, Issue 10, July 2006, Pages 1152-1160, 

Elsevier. 

www.elsevier.com or 

at www.sciencedirect.com

Denmark

Wind Integration, 

Heat Pumps

Meibom, P., Kiviluoma, J., Barth, R., Brand, H., Weber, 

C., Larsen, H., Value of electrical heat boilers and heat 

pumps for wind power integration, European Wind 

Energy Conference (EWEC), 27 February – 2 March, 

2006, Athens, Greece. 

www.risoe.dk/rispubl/art/2007_76.pdf

Denmark

Wind Integration, 

Heat Pumps

Meibom, P., Kiviluoma, J., Barth, R., Brand, H., Weber, 

C., Larsen, H.V., (2007). Value of electric heat boilers 

and heat pumps for wind power integration, Risoe 

National Laboratory, 2007.

Denmark

Wind Power 

Variability, Wind 

Integration

Meibom, P., Weber, C., Barth, R., Brand, H., Operational 

costs induced by fluctuating wind power production in 

Germany and Scandinavia, pp 133-154, In: Swider, D., 

Voss, A. (Eds), Deliverable D5b – Disaggregated system 

operation cost and grid extension cost caused by 

intermittent RES-E grid integration, GreenNet-EU27, 

2006. 

www.risoe.dk/rispubl/reports/ris-r-1608_196-

205.pdf

Denmark

Wind Integration, 

Energy Markets

Pedersen, J.; Eriksen, P.B.; Orths, A., 2006. Market 

Impacts of Large-Scale System Integration of Wind 

Power, European Wind Energy Conference EWEC 2006, 

Athens, Greece.

Denmark

Assortment of 

Papers and Topics see risoe.dk wind energy publications list
IEA Wind Task 24 Final Report, Vol. 1

109

Country/ continent 

(leading author) Topic Reference Link

Europe

Wind Integration, 

Systems Analysis

Ackermann, T.; Centeno-Lopez, E.; and Söder, L. Grid 

Issues for Electricity Production Based on Renewable 

Energy Sources in Spain, Portugal, Germany, and United 

Kingdom. Fritzes - Statens offentliga utredningar, 2008, 

Appendix to SOU 2008:13

Europe

Wind Integration, 

Systems Analysis

Eriksen, P B, Ackermann, T, Abildgaard, H, Smith, P, 

Winter, W, Garcia, J R, 2005. System operation with high 

wind penetration. The transmission challenges of 

Denmark, Germany, Spain and Ireland. IEEE power & 

energy magazine, nov/dec 2005. 

ieeexplore.ieee.org/iel5/8014/32593/015246

22.pdf?tp=&arnumber=1524622&isnumber=3

2593

Europe Wind Integration

ETSO, 2007. Balance management harmonisation and 

integration. 4th report, January, 2007.

Europe Wind Integration

EWEA, 2005. Large scale integration of wind energy in 

the European power supply: analysis, issues and 

recommendations. A report by EWEA (December 2005). 

www.ewea.org

Europe Wind Integration

EWEA, 2005. Large scale integration of wind energy in 

the European power supply: analysis, issues and 

recommendations. Electrical Grids and Wind Power: the 

present situation in Europe. 

www.ewea.org

Europe Wind Integration

EWIS, 2007. European Wind Integration Study final 

report phase I, 2007. 

Europe Wind Integration

DeMeo E A, Grant W, Milligan M, Schuerger M J, Wind 

plant integration: costs, status and issues, IEEE power & 

energy magazine, nov/dec 2005.

Europe

Wind- Hydro 

Systems

Luickx, P.J., Delarue, E.D., D’haeseleer, W.D., (2009). 

The Examination of Different Energy Storage Methods 

For Wind Power Integration, KULeuven Energy Institute, 

2009. 

www.mech.kuleuven.be/energy/resources/d

ocs/papers/pdf/WP%20EN2008-007.pdf

Europe

Wind Integration, 

Wind-Hydro, 

Systems Analysis

Nordel Wind Group, 2008. Wind Power in Nordel -

system impact for the year 2008.

Europe Systems Analysis

UCTE 2005: UCTE System Adequacy Forecast 2006 -

2016, Dec. 2005
IEA Wind Task 24 Final Report, Vol. 1

110

Country/ continent 

(leading author) Topic Reference Link

Finland Wind Integration

Holttinen, H, 2004. The impact of large scale wind power 

production on the Nordic electricity system. VTT 

Publications 554. Espoo, VTT Processes, 2004. 82 p. + 

app. 111 p. 

www.vtt.fi/inf/pdf/publications/2004/P554.pdf

Finland Wind Integration

Holttinen, H, 2005. Impact of hourly wind power 

variations on the system operation in the Nordic 

countries. Wind Energy, vol. 8, 2, ss. 197 – 218.

Finland

Wind Integration, 

Energy Markets

Holttinen, H, 2004 Optimal Electricity Market for Wind 

Power, Energy Policy 33

Finland

Wind Integration, 

Wind Forecasts

Holttinen, Hannele et.al. 2006. Prediction Errors and 

Balancing Costs for Wind Power Production in Finland, 

Global Wind Power Conference, Adelaide, Australia, 

September.

Finland

Wind Integration, 

Wind-Hydro

Holttinen, Hannele; Koreneff, Göran. 2007. Imbalance 

costs of wind power for a hydro power producer in 

Finland. Proceedings. European Wind Energy 

Conference EWEC2007. Milan, Italy, 7 - 10 May, 2007. 

European Wind Energy Association, EWEA. 

www.ewec2007proceedings.info/allfiles2/69

9_Ewec2007fullpaper.pdf

Finland Wind Integration

Holttinen, H, Vogstad, K-O, Botterud, A, Hirvonen, R, 

2001. Effects of Large-Scale Wind Production on the 

Nordic Electricity Market. Proceedings of European Wind 

Energy Conference, EWEC'01. Copenhagen, DK, 2 - 6 

July 2001. CD-ROM. European Wind Energy Association

Finland

Wind Integration, 

Wind-Hydro

Kiviluoma, Juha and Holttinen, Hannele. Impacts of Wind 

Power on Energy Balance of a Hydro Dominated Power 

System, VTT Technical Research Centre of Finland, 

VTT, Finland. 

www.vtt.fi/publications/index.jsp

Finland Wind Integration

Kiviluoma, Juha; Meibom, Peter; Holttinen, Hannele. 

2006. The operation of a regulation power market with 

large wind power penetration. Nordic Wind Power 

Conference – NWPC’2006. Grid Integration and 

Electrical Systems of Wind Turbines and Wind Farms. 

Hanasaari, Espoo, Finland, 22 - 23 May 2006
IEA Wind Task 24 Final Report, Vol. 1

111

Country/ continent 

(leading author) Topic Reference Link

Finland

Wind Integration, 

Wind-Hydro

Kiviluoma, Juha and Meibom, Peter and Holttien, 

Hannele 2006. Modelling of Hydro and Wind Power In 

The Regulation Market, VTT Technical Research Centre 

of Finland, VTT, Finland, May. 

www.vtt.fi/publications/index.jsp

Finland

Wind Integration, 

Energy Markets

Nordel, 2005. Enhancing Efficient Functioning of the 

Nordic Electricity market, NORDEL, February 2005. 

Finland

Wind Integration, 

Power Systems

Soder, L. and Holttinen, H. (2008). On methodology for 

modeling wind power impact on power systems, Int. J. 

Global Energy Issues, Vol 29, Nos. 1/2 pp. 181-198

Finland Wind Integration

Soder, L. et al. 2007, Experience from Wind Integration 

in Some High Penetration Areas, IEEE Transactions on 

Energy Conversion, Vol. 22, No. 1. 

ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnu

mber=4105991&arnumber=4106017&count=

29&index=1

Germany

Wind Integration, 

Systems Analysis

Burges, K., De Broe, A. M. & Feijoo, A. Advanced wind 

farm control according to Transmission System Operator 

requirements. European Wind Energy Conference, 

EWEC’03 Madrid, Spain, 16.–20.6.2003.

Germany Wind Integration

DENA, 2005. Planning of the Grid Integration of Wind 

Energy in Germany, Onshore and Offshore up to the 

year 2020 (dena Grid study). Deutsche Energie-Agentur 

Dena, March 2005. 

www.dena.de/themen/themareg/projektarchiv

Germany

Wind Integration, 

Wind Forecasts

Ensslin, C. 2006: The Influence of Modeling Accuracy on 

the Determination of Wind Power Capacity Effects and 

Balancing Needs, PhD Thesis, Kassel University Press 

2006. 

www.unikassel.de/upress/publi/schriftenreihe.php?ern

euerbare_energien.html

Germany

Wind Integration, 

Wind Forecasts

Ensslin, C., Ernst, B., Rohrig, K., Schlogl, F., 2003. 

Online-Monitoring and Prediction of Wind Power in 

German Transmission System Operation Centres. 

WWEC 2003 - World Wind Energy Conference, Cape 

Town, South Africa, 2003. 

www.regie-energie.qc.ca/audiences/3526-

04/MemoiresParticip3526/Memoire_CCVK_1

4_EWEC_03_Be_En_HK_Ro.pdf

Germany

Wind Integration, 

Systems Analysis

Erlich, I., Winter, W., Dittrich, A., 2006. Advanced Grid 

Requirements for the Integration of Wind Turbines into 

the German Transmission System. IEEE PES, Montreal, 

2006. 

ieeexplore.ieee.org

(subscription required)
IEA Wind Task 24 Final Report, Vol. 1

112

Country/ continent 

(leading author) Topic Reference Link

Germany Wind Integration

Ernst, B. 1999. Analysis of wind power ancillary services 

characteristics with German 250 MW wind data. NREL 

Report No. TP-500-26969. 38 p. www.nrel.gov/publications

Germany Wind Forecasts

Focken, U., Lange, M., Waldl, H.-P. 2001. Previento – A 

Wind Power Prediction System with an Innovative 

Upscaling Algorithm, In: Proceedings of EWEC’01, 2nd–

6th July, 2001, Copenhagen. pp. 826–829.

Germany Wind Forecasts

Focken, Ulrich, 2007. OPTIMAL COMBINATION OF 

EUROPEAN WEATHER MODELS FOR IMPROVED 

WIND POWER PREDICTIONS. In: Proceedings of 

EWEC’07, 7–10th May, 2007, Milan, Italy. 

Germany

Distributed 

Generation, Wind 

Integration

Giebel, G., 2000: On the Benefits of Distributed 

Generation of Wind Energy in Europe; PhD Thesis, Carl 

von Ossietzky Universität, Oldenburg, 2000. 

www.drgiebel.de/thesis.htm

Germany Wind Forecasts

Giebel, G, Brownsword, R, Kariniotakis, G, 2003. The 

State-of-the-art in Short-term prediction of wind power. A 

literature overview. EU project ANEMOS (ENK5-CT2002-00665). 

anemos.cma.fr/download/publications/pub_2

003_paper_EWEC03_SOTAGiebel.pdf

Germany Wind Integration

Giebel, G, 2007. A Variance Analysis of the Capacity 

Displaced by Wind Energy in Europe. Wind Energy 2007; 

10:69-79. 

www.interscience.wiley.com

Germany

Wind Integration, 

Energy Markets

Krauss, C., Graeber, B., M. Lange, 2006. Integration of 

18 GW Wind Energy into the Energy Market - Practical 

Experiences in Germany, Workshop on Best Practice in 

the Use of Short-term Forecasting of Wind Power, Delft 

2006.

Germany Wind Integration

ISET, 2005. Wind Energy Report Germany 2005, ISET, 

Kassel, 2005.

Germany Wind Forecasts

ISET, 2006. Private communication with Cornel Ensslin 

for the standard deviation of variations time series. 

www.renknow.net

(search keyword “time series”)

Germany Wind Forecasts

Rohrig, K. and Lange, B., 2006. Application of Wind 

Power Prediction Tools for Power System Operations, 

presented at the 2006 IEEE Power Engineering Society 

General Meeting, Montreal, Canada, 2006. 

ieeexplore.ieee.org
IEA Wind Task 24 Final Report, Vol. 1

113

Country/ continent 

(leading author) Topic Reference Link

Germany

Wind Integration, 

Wind Forecasts

Rohrig, K. and Lange, B., 2007. Improvement of the 

Power System Reliability by Prediction of Wind Power 

Generation, IEEE PES general Meeting 2007, 

Tagungsband, Tampa, FL USA 06/2007. 

ieeexplore.ieee.org

Germany Wind Forecasts

Rohrig, K., Sassnick, Y., Styczynski, Z., Völzke, R., 2006. 

Experiences with operation of wind farms using wind 

forecasting tools, CIGRE 2006, Tagungsband, Palais de 

Congres, Paris 08/2006

Germany Wind Integration

Rohrig, K. et al., 2005. Advanced Control Strategies to 

Integrate German Offshore Wind Potential into Electrical 

Energy Supply, 5th International Workshop on LargeScale Integration of Wind Power and Transmission 

Networks for Offshore Wind Farms, Tagungsband, 

Glasgow 04/2005

Greece Wind-Hydro

Bakos, George, 2002. Feasibility study of a hybrid 

wind/hydro power-system for low-cost electricity 

production. Applied Energy 72 pp.599-608, 2002. 

www.elsevier.com/locate/apenergy

Greece Wind-Hydro

Kaldellis, J.K., Kavadias, K.A., Vlachou, D.S., Electricity 

Load Management of APS Using Wind-Hydro Solution. 

Lab of Soft Energy Applications and Environmental 

Protection. 

www.theiet.org

Greece Wind-Hydro

Kaldellis, J.K., 2001, Parametrical Investigation of the 

Wind-Hydro Electricity Production Solution Aegean 

Archipelago, Energy and Conservation Management

International Wind Integration

Bryans, Leslie et al., 2006. Electric Power System 

Planning with the Uncertainty of Wind Generation, 

CIGRE Working Group. April, 2006.

International Wind Integration

Ensslin, C., Milligan, M., Holttinen, H., O’Malley, M.J. and 

Keane, A. Current Methods to Calculate Capacity Credit 

of Wind Power, IEA Collaboration, IEEE PES General 

Meeting, Pittsburgh, July 2008.
IEA Wind Task 24 Final Report, Vol. 1

114

Country/ continent 

(leading author) Topic Reference Link

International Wind Forecasts

Ernst, Bernhard et al. Predicting the Wind: Models and 

Methods of Wind Forecasting for Utility Operations 

Planning, IEEE Power and Energy Magazine, Vol. 5, 

Num. 6, Nov./Dec. 2007. 

ieeexplore.ieee.org/iel5/8014/4382976/0438

3126.pdf?tp=&arnumber=4383126&isnumber

=4382976

International Wind Integration

GWEC, 2005. Wind Force 12, A blueprint to achieve 12% 

of the world's electricity from wind power by 2020. www.ewea.org

International Wind Integration

Holttinen, Hannele et al., 2006. Design and Operation of 

Power Systems with large Amounts of Wind Power, first 

results of IEA collaboration. Global Wind Power 

Conference, Adelaide, Australia. September 18-21, 2006.

International Wind Integration

IEA. 2007. State of the Art Task 25 Report: Design and 

operation of power systems with large amounts of wind 

power. 

www.ieawind.org/AnnexXXV/Publications/W8

2.pdf

International Wind Integration

IEA: Variability of wind power and other renewables. 

Management options and strategies. 2005. 

International

Wind Integration, 

Power Char.

IEC 61400-21, 2001. Wind turbine generator systems -

Part 21: Measurement and assessment of power quality 

characteristics of grid connected wind turbines, Ed. 1.0, 

International Standard, 2001.

International Emissions

Sims, Ralph E. H. et al., 2003. Carbon emission and 

mitigation cost comparisons between fossil fuel, nuclear 

and renewable energy resources for electricity 

generation. Energy Policy 31 (2003), pp. 1315-1326. 

www.elsevier.com/locate/enpol

International Wind Integration

Sørensen, P.; Norheim, I.; Meibom, P.; Uhlen, K., 

Simulations of wind power integration with 

complementary power system planning tools. Electric 

Power Syst., Volume 78, Issue 6/, /June 2008/, /Pages 

1069-1079./

International

Wind Integration, 

Power Systems

Tande J O, Muljadi E, Carlson O, Pierik J, Estanqueiro A, 

Sørensen P, O'Malley M, Mullane A, Anaya-Lara O, 

Lemstrom B (2004) Dynamic models of wind farms for 

power system studies - status by IEA Wind R&D Annex 

21, European Wind Energy Conference (EWEC’2004), 

22-25 November, London, UK. 

www.energy.sintef.no/wind/iea_dynamic_mo

dels_EWEC'04_paper.pdf
IEA Wind Task 24 Final Report, Vol. 1

115

Country/ continent 

(leading author) Topic Reference Link

Ireland Wind Integration

Bazilian, M., Denny, E. and O’Malley, M.J., Challenges of 

Increased Wind Energy Penetration in Ireland, Wind 

Engineering, vol. 28, pp. 43-56, 2004.

Ireland Wind Integration

Bryans, L., J. McCann, Smith, P. and O’Malley, M.J., All 

island Renewable Grid Study, IEEE PES, General 

Meeting, Tampa, June 2007. 

ieeexplore.ieee.org

Ireland

Wind Integration, 

Power Systems

Burke, D.J. and O’Malley, M.J., Optimal Wind Power 

Location on Transmission Systems – A Probabilistic 

Load Flow Approach, IEEE PMAPS, Puerto Rico, May, 

2008. 

ieeexplore.ieee.org

Ireland Wind Integration

Denny, E., Bryans, G., Fitzgerald, J. and O’Malley, M.J., 

2006. A Quantitative Analysis of the Net Benefits of Grid 

Integrated Wind, IEEE PES, General Meeting, Montreal, 

June 2006.

ieeexplore.ieee.org

Ireland

Wind Integration, 

Energy Markets, 

Emissions

Denny, E and O’Malley, M. J., 2005. Impact of increasing 

levels of wind generation in electricity markets on 

emissions reduction, Proceedings of the 7th IAEE 

European Energy Conference - European Energy 

Markets in Transition, Bergen, Norway, Aug, 2005. 

Ireland

Wind Integration, 

Power Systems, 

Emissions

Denny, E. and O’Malley, M.J., Impact of wind generation 

on emissions under alternative power system operation 

approaches, Proceedings of the University Power 

Engineering Conference, Cork, Sept, 2005.

Ireland Wind Integration

Denny, E. and O’Malley, M.J. Quantifying the Total Net 

Benefits of Grid Integrated Wind, IEEE Transactions on 

Power Systems, Vol. 22, no. 2, pp. 605 -615, 2007. Also 

presented at the IEEE Power Engineering Society, 

General Meeting, Tampa, June, 2007. 

ieeexplore.ieee.org

Ireland

Wind Integration, 

Power Systems, 

Emissions

Denny, E., and O’Malley, M.J., Wind Generation, Power 

System Operation and Emissions Reduction IEEE 

Transactions on Power Systems, Vol. 21, pp. 341 – 347, 

2006. 

ieeexplore.ieee.org

Ireland Wind Integration

Department of Communications, Energy and Natural 

Resources, 2008. All Island Grid Study. www.dcenr.gov.ie
IEA Wind Task 24 Final Report, Vol. 1

116

Country/ continent 

(leading author) Topic Reference Link

Ireland

Wind Integration, 

Power Systems

Doherty, R., Denny, E. and O’Malley, M.J., System 

operation with a significant wind power penetration, IEEE 

PES General Meeting, Denver 2004. 

ieeexplore.ieee.org

Ireland Wind Integration

Doherty, R, Bryans, L., Gardner, P., O’Malley, M.J., Wind 

penetration studies on the Island of Ireland, Wind 

Engineering, vol. 28, pp. 27-42, 2004.

Ireland Wind Integration

Doherty, R. and O’Malley, M.J., Establishing the role that 

wind generation may have in future generation portfolios, 

IEEE Transactions on Power Systems, Vol. 21, pp. 1415 

– 1422, 2006. 

ieeexplore.ieee.org

Ireland

Wind Integration, 

Power Systems

Doherty, R., Lalor, G. and O’Malley,M.J., Frequency 

Control in Competitive Electricity Market Dispatch, IEEE 

Transactions on Power Systems, Vol. 20, pp. 1588 -

1596, 2005. 

ieeexplore.ieee.org

Ireland

Wind Integration, 

Emissions

Doherty, R. and O'Malley, M.J. 2005. “Generation 

portfolio analysis for a carbon constrained and uncertain 

future”, Proceedings of International Conference on 

Future Electricity Networks, Amsterdam, Nov. 2005. 

ieeexplore.ieee.org

Ireland Wind Integration

Doherty, R., O’Malley, M.J., 2005. New approach to 

quantify reserve demand in systems with significant 

installed wind capacity, IEEE Transactions on Power 

Systems, Vol. 20, pp. 587 -595, 2005. 

ieeexplore.ieee.org

Ireland Wind Integration

Doherty, R. and O’Malley, M., Quantifying Reserve 

Demands due to Increasing Wind Power Penetration, 

IEEE Power Tech, Bologna, Italy, June, 2003.

ieeexplore.ieee.org

Ireland Wind Integration

ESBI, 2004. Renewable Energy Resources for Ireland 

2010 & 2020. Sustainable Energy Ireland, 2004.

Ireland Wind Integration

ESBNG, ESB National Grid, 2004. Impact of wind power 

generation in Ireland on the operation of conventional 

plant and the economic implications, February 2004. 

Ireland Wind Integration

Feeley, C., Bryans, A.G., Nyamdash, B., Denny, E., 

O’Malley, M.J., The Viability of Balancing Wind 

Generation with Storage, IEEE PES General Meeting, 

Pittsburgh, July 2008.
IEA Wind Task 24 Final Report, Vol. 1

117

Country/ continent 

(leading author) Topic Reference Link

Ireland Wind Integration

Fox, B. et al. 2007. Managing the variability of wind 

energy with heating load control, IET Intl. Conf. on 

Information and Communication Technology in Electrical 

Sciences, Chennai, India, December 2007

Ireland Wind Integration

Fox, B., Littler, T. and Flynn, D., 2005 Measurementbased estimation of wind farm inertia, PowerTech 2005, 

St. Petersburg, Russia, 27-30 June 2005

Ireland Wind Integration

Fox, B. and Flynn, D., 2005. Wind intermittency –

mitigation measures and load management, PowerTech 

2005, St. Petersburg, Russia, 27-30 June 2005

Ireland Wind Integration

Fox, B., Bryans, L., Flynn, D., Jenkins, N., Millborrow, D., 

O’Malley, M., Watson, R. and Anaya-Lara, Wind power 

integration; Connection and system operational aspects, 

IET Power and Energy Series, 2007.

Ireland

Wind Integration, 

Power Systems

Gardner, P., et al., 2003. The Impacts of Increased 

Levels of Wind Penetration on the Electricity Systems of 

the Republic of Ireland and Northern Ireland. 

Commission for Energy Regulation

Ireland

Wind Integration, 

Power Systems

Horne, J., Flynn, D., and Littler, T., Frequency stability 

issues for island power systems, IEEE PES Power 

Systems Conference & Exposition, October 2004. 

www.ucc.ie/academic/civil/staff/brian/CER03

024.pdf

Ireland Wind Integration

Ilex, UMIST, UCD and QUB, 2004. Operating reserve 

requirements as wind power penetration increases in the 

Irish electricity system. Sustainable Energy Ireland, 2004. 

www.sei.ie/uploadedfiles/InfoCentre/IlexWind

Reserrev2FSFinal.pdf

Ireland Wind Integration

Ilex Energy, Strbac, G, 2002. Quantifying the system 

costs of additional renewables in 2020. DTI, 2002. 

Ireland

Distributed 

Generation, Wind 

Integration

Kennedy, J. et al. 2007 Distributed diesel generation to 

facilitate wind power integration, IEEE PowerTech, 

Switzerland 2007.Denny, E., Malaguzzi Valeri, L., Fitz 

Gerald, J. and O’Malley, M.J. “Carbon prices and asset 

degradation – a costly combination for electric power 

systems”, Proceedings of 30th International Association 

for Energy Economics, Wellington, New Zealand, 18-21, 

February, 2007.
IEA Wind Task 24 Final Report, Vol. 1

118

Country/ continent 

(leading author) Topic Reference Link

Ireland

Distributed 

Generation, Wind 

Integration

Kennedy, J. et al. Distributed generation as a balancing 

tool for wind generation, IET Renew, Power Gener., Vol. 

1(3), 2007, pp. 167-174

Ireland

Wind Integration, 

Power Systems

Smith, P., O’Malley, M.J., Mullane, A., Bryans, L., Denic, 

D.P., Bell, K.R.W., Meibom, P., Barth, R., Hasche, B., 

Brand, H., Swider, D.J., Burges, K. and Nabe, C., 

Technical and Economic Impact of High Penetration of 

Renewables in an Island Power System, CIGRE, C6-

102, Paris, 2008.

Ireland

Wind Integration, 

Wind Forecasts

Tuohy, A., Denny, E. and M.J. O’Malley, Allocation of 

System Reserve Based on Standard Deviation of Wind 

Forecast Error, Nordic Wind Power Conference, 

Denmark, November, 2007.

Ireland

Wind Integration, 

Power Systems

Tuohy, A., Denny, E., and O’Malley, M.J., Rolling unit 

commitment for systems with significant installed wind 

capacities, IEEE Power Tech, Lausanne, Switzerland, 

July, 2007.

Ireland

Wind Integration, 

Power Systems

Tuohy, A., Meibom, P. and O’Malley, M.J., Benefits of 

Stochastic Scheduling for Power Systems with 

Significant Installed Wind Power, IEEE PMAPS, Puerto 

Rico, May, 2008.

Ireland

Wind Integration, 

Power Systems

Tuohy, A., Denny, E., Meibom, P., Barth, R., O’Malley, 

M.J., Operating the Irish Power System with Increased 

Levels of Wind Power, IEEE PES General Meeting, 

Pittsburgh, July 2008.

Ireland Wind Integration

Twohig, S., Burges, K., Nabe, C., Polaski K., and 

O’Malley, M.J., Ultra High Wind Energy Penetration in an 

Isolated Market, IEEE PES General Meeting, Pittsburgh, 

July 2008.

Mexico Wind-Hydro

Jaramillo, O.A. and Borja, M.A. and Huacuz, J.M. 2004. 

Using Hydropower to Complement Wind Energy: A 

Hybrid System to Provide Firm Power, Renewable 

Energy, 29, pp. 1887-1909. February. 

www.elsevier.com/locate/renene
IEA Wind Task 24 Final Report, Vol. 1

119

Country/ continent 

(leading author) Topic Reference Link

Netherlands

Eleveld, H.F., Enslin, J.H.R., Groeman, J.F., van 

Oeveren, K.J., van Schaik, M.A.W., 2005: Connect 6000 

MW-II: Elektrische infrastructuur op zee. Kema 

40510025-TDC 05-485000, september 2005.

Netherlands

Jansen, C.P.J. de Groot R.A.C.T.: Connect 6000 MW: 

Aansluiting van 6000 MW offshore windvermogen op het 

Nederlandse elektriciteitsnet. Deel 2: Net op land. Kema 

40330050-TDC 03-37074B. oktober 2003.

Netherlands Wind Integration

Hagstrøm E, Norheim I, Uhlen K, Large-scale wind 

power integration in Norway and impact on damping in 

the Nordic grid, Wind Energy 2005; 8(3) pp 375-384.

Netherlands

Wind Integration, 

Power Systems

Kling, W.L., et al., 2007. Transmission and System 

Integration of Wind Power in the Netherlands, 

Proceedings of the IEEE PES General Meeting, Tampa, 

24-28 June, 2007, 6 pp. 

ieeeexplore.ieee.org

Netherlands Wind Integration

Palsson M T, Toftevaag T, Uhlen K, Tande J O, Largescale Wind Power Integration and Voltage Stability Limits 

in Regional Networks, Proceedings of 2002 IEEE-PES 

Summer Meeting

Netherlands Wind Integration

Palsson M T, Toftevaag T, Uhlen K, Tande J O, Control 

Concepts to Enable Increased Wind Power Penetration. 

Proceedings of IEEE-PES Meeting, Toronto 13-18 July 

2003

Netherlands

Wind Integration, 

Power Systems

Slootweg, J.G., Kling, W.L. 2003, The Impact of Large 

Scale Wind Power Generation on Power System 

Oscillations, Electric Power Systems Research 67

Netherlands

Wind Integration, 

Power Systems

Ummels, B.C., et al., 2008. Energy Storage Options for 

System Integration of Offshore Wind Power in the 

Netherlands, Proceedings of European Wind Energy 

Conference, Brussels, 3-7 April 2008, 10 pp.

Netherlands Wind Integration

Ummels, B.C., et al., 2007. Impacts of Wind Power on 

Thermal Generation Unit Commitment and Dispatch, 

IEEE Transactions on Energy Conversion, vol. 22, issue 

1, March 2007, pp. 44-51. 

ieeeexplore.ieee.org
IEA Wind Task 24 Final Report, Vol. 1

120

Country/ continent 

(leading author) Topic Reference Link

Netherlands Wind Integration

Ummels, B.C., et al., 2008. Integration of Large-Scale 

Wind Power and Use of Energy Storage in the 

Netherlands’ Electricity Supply, IET Renewable Power 

Generation, vol. 2, issue 1, March 2008, pp. 34-46

Netherlands

Wind Integration, 

Energy Markets

Ummels, B.C., et al., 2006. Integration of Wind Power in 

the Liberalized Dutch Electricity Market, Wind Energy, 

Issue 9, no. 6, November-December 2006, pp. 579-590

Netherlands Wind Integration

Ummels, B.C., et al., 2006. System Integration of LargeScale Wind Power in the Netherlands, Proc. of IEEE PES 

General Meeting, Montreal, June 18-22, 2006, 8 pp. 

ieeeexplore.ieee.org

New Zealand

Wind-Hydro, 

Energy Markets

Pritchard, G.; Philpott, A. B.; and Neame, P.J. 

Hydroelectric reservoir optimization in a pool market. 

December, 2004. 

www.springerlink.com/content/3am5a6g8cg2

qpudj/fulltext.pdf

Norway Wind Forecasts

Berge, Erik, et al. Wind in Complex Terrain, A 

Comparison of WASP and two CFD models. 

windsim.com/documentation/papers_present

ations/0602_ewec/ewec_berge.pdf

Norway

Wind Integration, 

Power Systems

Di Marzio G, Fosso O, Uhlen K, Pálsson M P, Largescale wind power integration - voltage stability limits and 

modal analysis, 15th Power System Computation 

Conference, PSCC 2005, Liege

Norway

Wind Integration, 

Power Systems

Gjengedal, T, 2003, Integration of Wind Power and the 

Impact on Power System Operation, IEEE Conference 

on Power Engineering

Norway

Systems Analysis, 

Automatic 

Generation Control

Gjengedal, T. 2003, System Control of Large Scale Wind 

Power by use of Automatic Generation Control, 

CIGRE/IEEE PES International Symposium on Quality of 

Electric Power Delivery Systems, Montreal, October 

2003

Norway Wind Integration

Gjengedal, T, 2005. Large scale wind power farms as 

power plants. Wind Energy, Vol. 8, Issue 3, pp. 361-373

Norway Wind Integration

Hagstrøm E, Norheim I, Uhlen K, 2005. Large-scale wind 

power integration in Norway and impact on damping in 

the Nordic grid, Wind Energy 2005; 8(3) pp 375-384.
IEA Wind Task 24 Final Report, Vol. 1

121

Country/ continent 

(leading author) Topic Reference Link

Norway

Wind Integration, 

Wind-Hydro, 

Energy Markets

Korpaas, Magnus; Holen, Arne T.; and Hildrum, Ragne, 

2003. Operation and sizing of energy storage for wind 

power plants in a market system. International Journal of 

Electrical Power and Energy Systems, v25, n8, p599-

606, October, 2003.

Norway

Wind Integration, 

Wind-Hydro

Korpås M, Tande J O, Uhlen K, Gjengedal T, 2006. 

Planning and operation of large wind farms in areas with 

limited power transfer capacity. European Wind Energy 

Conference (EWEC), Athens, Greece, 27 February - 2 

March 2006. 

www.ewec2006proceedings.info/allfiles2/18

8_Ewec2006fullpaper.pdf

Norway

Wind Integration, 

Power Systems

Palsson M T, Toftevaag T, Uhlen K, Tande J O, 2003. 

Control Concepts to Enable Increased Wind Power 

Penetration. Proceedings of IEEE-PES Meeting, Toronto 

13-18 July 2003. 

ieeeexplore.ieee.org

Norway

Wind Integration, 

Power Systems

Palsson M T, Toftevaag T, Uhlen K, Tande J O, 2002. 

Large-scale Wind Power Integration and Voltage Stability 

Limits in Regional Networks, Proceedings of 2002 IEEEPES Summer Meeting

Norway

Wind- Hydro 

Integration

Suul, J.A., Uhlen, K., Undeland, T., (2008). Wind Power 

Integration in Isolated Grids enabled by Variable Speed 

Pumped Storage Hydropower Plant, in Proc. of IEEE 

International Conference on Sustainable Energy 

Technologies, Singapore, Nov., 2008

Norway Wind Integration

Tande J O, Uhlen K, 2004.Cost analysis case study of 

grid integration of larger wind farms, Wind engineering, 

volume 28, No3, 2004, pp 265-273

Norway Wind Integration

Tande, J.O., 2006. Impact of integrating wind power in 

the Norwegian power system. SINTEF report. 

Norway

Wind Integration, 

Wind-Hydro

Tande, John Olav and Korpas, Magnus 2006. Impact of 

Large Scale Wind Power on System Adequacy in a 

Regional Hydro-Based Power System With Weak 

Interconnections, Nordic Wind Power Conference, 

SINTEF Energy Research, Espoo, Norway, May.
IEA Wind Task 24 Final Report, Vol. 1

122

Country/ continent 

(leading author) Topic Reference Link

Norway

Wind Integration, 

Wind-Hydro

Tande, J.O. and Vogstad, Klaus-Ole, Operational 

Implications of Wind Power in a Hydro Based Power 

System, EWEC, Nice, France, March, 1999. 

www.stud.ntnu.no/~klausv

Norway

Wind-Hydro 

Integration

Troscher, T., Korpas, M., (2008). A Power Market Model 

for studying the Impact of Wind Power on Spot Prices, 

Proc. of 16th PSCC, Glasgow, Scotland, July 2008.

Norway Wind-Hydro

Vogstad, Klaus-Ole, Utilizing the complementary 

characteristics of wind power and hydropower through 

coordinated hydro production scheduling using the MultiArea Power Market Simulator model, in Proc. 2000 

Nordic Wind Energy Conference. 

www.stud.ntnu.no/~klausv

Norway

Wind-Hydro, 

Energy Markets

Vogstad, Klaus-Ole et al., System Benefits of 

Coordinating Wind Power and Hydropower in a 

Deregulated Market, in Proc. 2000 Nordic Wind Energy 

Conference. 

www.stud.ntnu.no/~klausv

Portugal

Wind Integration, 

Power Systems

de Almeida, R.G.; Castronuovo, E.D.; Lopes, J.A.P.; 

Optimum generation control in wind parks when carrying 

out system operator requests, IEEE Transactions on 

Power Systems, Volume 21, Issue 2, May 2006 

Page(s):718 – 725. 

ieeeexplore.ieee.org

Portugal

Wind Integration, 

Power Systems

de Almeida, R.G.; Pecas Lopes, J.A.; Barreiros, J.A.L.; 

Improving power system dynamic behavior through 

doubly fed induction machines controlled by static 

converter using fuzzy control, IEEE Transactions on 

Power Systems, Volume 19, Issue 4, Nov. 2004 

Page(s):1942 – 1950. 

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb

er=1350834

Portugal

Wind Integration, 

Power Systems

de Almeida, R.G.; Pecas Lopes, J.A.; Participation of 

Doubly Fed Induction Wind Generators in System 

Frequency Regulation, IEEE Transactions on Power 

Systems, Volume 22, Issue 3, Aug. 2007 Page(s):944 –

950. 

ieeeexplore.ieee.org

Portugal Power Systems

de Almeida, R.G, Pecas Lopes, J.A., , Primary frequency 

control participation provided by doubly fed induction 

wind generators. Proceedings do 16th PSCC em Liége, 

Bélgica, August 2005.
IEA Wind Task 24 Final Report, Vol. 1

123

Country/ continent 

(leading author) Topic Reference Link

Portugal Wind Integration

de Andrade, Mário C. J. and Pinto, Medeiros. Portuguese 

TSO strategy to integrate 3750 MW of Wind Power by 

2010 - Power System Operation with large Wind 

Capacity Integrated, INETI, Lisbon, 2005.

Portugal Wind Integration

Baptist, F., 2006. - Plan of Specific Reinforcement of the 

RNT up to 2010 for Reception of Production in Special 

Regimen, VI Days of Electrotécnica Engineering and 

Computers - IST, Lisbon, 2006.

Portugal

Wind Integration, 

Wind-Hydro

Brown, P. D.; PeÇas Lopes, J. A.; Matos, M. A.; 

Optimization of Pumped Storage Capacity in an Isolated 

Power System With Large Renewable Penetration, IEEE 

Transactions on Power Systems, Volume 23, Issue 2, 

May 2008 Page(s):523 – 531. 

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumbe

r=4476156

Portugal Wind-Hydro

Castronuovo, E.D., J.A. Peças Lopes. Bounding Active 

Power Generation of a Wind-Hydro Power Plant, 

Proceedings of the PMAPS-2004 (8th. International 

Conference on Probabilistic Methods Applied to Power 

Systems). September 13-16, 2004, Ames, Iowa, USA.

Portugal Wind-Hydro

Castronuovo, E.D. and J.A. Pecas Lopes, On the 

Optimization of the Daily Operation of Wind-Hydro Power 

Plant, IEEE Transactions on

Power Systems, vol. 19, pp. 1599-1606, Aug. 2004. 

ieeexplore.ieee.org/iel5/59/29221/01318699.

pdf?arnumber=1318699

Portugal Wind-Hydro

Castronuovo, E.D., J.A. Peças Lopes. Optimal Operation 

and Hydro Storage Sizing of a Wind-Hydro Power Plant, 

International Journal of Electrical Power and Energy 

Systems, vol. 26/10, pp 771-778, December, 2004.

Portugal

Power Systems, 

Power 

Characteristics

Estanqueiro, A. I., Tande, J.O., and Lopes, J.A. Pecas. 

Assessment of Power Quality Characteristics of Wind 

Farms, Proc. IEEE PES meeting, Tampa, Florida. June, 

2007. 

ieeeexplore.ieee.org

Portugal Wind Integration

Estanqueiro, A.I. et al. Barriers (and Solutions...) to Very 

High Wind Penetration in Power Systems, Proc. IEEE 

PES meeting, Tampa, Florida, Junho, 2007. 

ieeeexplore.ieee.org
IEA Wind Task 24 Final Report, Vol. 1

124

Country/ continent 

(leading author) Topic Reference Link

Portugal Wind Integration

Estanqueiro, A., 2006. Study on the Portuguese spatial 

correlation and smoothing effect of fast wind power 

fluctuations. INETI, Private communication, December, 

2006. 

Portugal Wind Integration

Estanqueiro, A., R. Castro, P. Flores, J. Ricardo, M. 

Pinto, R. Rodrigues, J. Peças Lopes. How to prepare a 

power system for 15% wind energy penetration: the 

Portuguese case study. Wind Energy, Vol. 11, Number 

1,Jan. 2008 Page(s) 75 – 84

Portugal Wind Integration

Fidalgo, J.N.; Pecas Lopes, J.A.; Miranda, V.; Neural 

networks applied to preventive control measures for the 

dynamic security of isolated power systems with 

renewables, IEEE Transactions on Power Systems, 

Volume 11, Issue 4, Nov. 1996 Page(s):1811 – 1816. 

ieeeexplore.ieee.org

Portugal Power Systems

Franco Marques, P.J., Pecas Lopes, J.A., Impact of the 

Use of FACTS to Increase Robustness of Operation in 

Grids with Large Scale Wind Generation, in NORDIC 

WIND POWER CONFERENCE, Espoo, Finland, May, 

2006.

Portugal Power Systems

Franco Marques, P.J., Pecas Lopes, J.A., Improving 

power system dynamical behavior through dimensioning 

and location of STATCOMs in systems with large scale 

wind generation, in Power Tech, Lausanne, Switserland, 

July, 2007.

Portugal Power Systems

Franco Marques, P.J., Pecas Lopes, J.A., Use of 

Simulated Annealing for optimizing capacity and location 

of STATCOM in Grids with Large Scale Wind 

Generation, in POWERENG, Setubal, Portugal, April, 

2007.

Portugal

Wind Integration, 

Wind Forecasts

INEGI, 2002. Wind Resource Variability Patterns in 

Continental Portugal, INEGI – Instituto de Engenharia 

Mecânica e Gestão Industrial – University of Oporto, 

commissioned by REN, Rede Eléctrica Nacional, SA
IEA Wind Task 24 Final Report, Vol. 1

125

Country/ continent 

(leading author) Topic Reference Link

Portugal Wind Integration

Imaz, Luíz et al., 2006. Admisible wind generation in the 

Iberian peninsular electric system by 2011 (in Spanish or 

Portuguese) – MIBEL, July 2006.

Portugal

Wind Integration, 

Power Systems

Mendonca, A, Pecas Lopes, J.A., , A Multicriteria 

Approach to Identify the Adequate Wind Power 

Penetration in Isolated Grids, Proceedings of 

MedPower'04 - 4th Mediterranean IEE Conference and

Exhibition on Power Generation, Transmission and 

Distribution, Lemesos, Cyprus, Novembro de 2004.

Portugal Wind Integration

Mendonça, Â., Peças Lopes, J.A.. Impact of Large Scale 

Wind Power Integration on Small Signal Stability, 

Proceedings of FPS 2005, International Conference on 

Future Power Systems, November 2005.

Portugal

Wind Integration, 

Power Systems, 

Wind Forecasts

Moyano, Carlos Fabian, Pecas Lopes, J.A, A Unit 

Commitment and Dispatch for a Wind Park Considering 

Wind Power Forecast, Proceedings of ICREPQ'07 -

INTERNATIONAL CONFERENCE ON RENEWABLE 

ENERGIES AND POWER QUALITY (ICREPQ'07), vol.1, 

no.1, pp.1-6, Sevilha, Espanha, Março, 2007.

Portugal

Wind Integration, 

Power Systems

Moyano, Carlos Fabian, Pecas Lopes, J.A, Unit 

Commitment and Dispatch Strategies for a Wind Park,

Proceedings of POWERENG 2007 - International 

Conference on Power Engineering, Energy and Electrical 

Drives, vol.1, no.1, pp.1-6, Setubal, Portugal, Abril, 2007.

Portugal

Wind Integration, 

Power Systems

Moyano, Carlos Fabian, Pecas Lopes, J.A, , Using an 

OPF like Approach to Define the Operational Strategy of 

a Wind Park under a System Operator Control, IEEE 

Lausanne Power Tech 2007, Lausanne, Switzerland, 

Julho, 2007.

Portugal Wind Integration

Paiva, Sucena et al., 2004. Limits of wind generation to 

connect to the public networks under the stability point of 

view (in Portuguese), October, 2004.
IEA Wind Task 24 Final Report, Vol. 1

126

Country/ continent 

(leading author) Topic Reference Link

Portugal Power Systems

Pecas Lopes, J.A, New Technical and Conceptual 

Solutions to Allow a Larger Increase of the Integration of

Intermittent Energy Sources in Power Systems, X 

SYMPOSIUM OF SPECIALISTS IN ELECTRIC 

OPERATIONAL AND EXPANSION PLANNING, X 

SEPOPE, Florianopolis, May, 2006.

Portugal Power Systems

Pecas Lopes, J.A, Vasconcelos, H., Security 

Assessment of Interconnected Systems Having Large 

Wind Power Production, CIGRE SYMPOSIUM: Power 

Systems with Dispersed Generation, Athens, Greece, 

April, 2005;

Portugal

Wind Integration, 

Power Systems

Pecas Lopes, J.A, Technical and Commercial Impacts of 

the Integration of Wind Power in the Portuguese System 

Having in Mind the Iberian Electricity Market, 

Proceedings do IEEE PowerTech2005 - St. Petersburg 

Power Tech 2005, St. Petersburg, Russia, June, 2005.

Portugal Wind Integration

Ricardo, João et al., 2006. National Goals For 

Renewable Generation In Portugal An Organizational 

And Technical Challenge From The Point Of View Of The 

Transmission System Operator - CIGRÉ SESSION, 

2006.

Portugal Wind Integration

Ricardo, João et al., 2005. First Phase-Shifting 

Autotransformers (PSAT) for the 400 kV Portuguese 

Network – 1st International Conference on Electrical 

Power Transmission, Algéria, 2005

Portugal Wind Integration

Ricardo, João et al., 2005. Study of Transitory Stability of 

the Portuguese net of transport of electric energy with

raised volumes of aeolian production - XI Encuentro 

Regional IberoAmericano del CIGRÉ-XI ERIAC, 2005.

Portugal Wind Forecasts

Rodrigues, A., et al. EPREV - A WIND POWER 

FORECASTING TOOL FOR PORTUGAL, EWEC 2007, 

Milan, Italy. May, 2007.
IEA Wind Task 24 Final Report, Vol. 1

127

Country/ continent 

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Portugal Wind Integration

Rodriguez-Bobada, F.; Reis Rodriguez, A.; Ceña, A.; and 

Giraut, E., Study of wind energy penetration in the 

Iberian peninsula. European Wind Energy Conference 

(EWEC), 27 February – 2 March, 2006, Athens, Greece. 

www.ewec2006proceedings.info/allfiles2/74

3_Ewec2006fullpaper.pdf

Portugal Systems Analysis

da Silva, A. M. Leite, et al. Application of Monte Carlo 

Simulation to Generating System Well-Being Analysis 

Considering Renewable Sources, Proceedings of 

PMAPS'2004 - 8th International Conference on PMAPS 

2004. Ames, USA, September, 2004.

Portugal

Wind Forecasts, 

Power Systems

Trancoso, Ana Rosa, et al. Comparative evaluation of 

wind power forecasts for Portuguese transmission 

system operator, EWEC 2008, Brussels Expo, Belgium, 

March 31 - April 3

Portugal

Wind Integration, 

Wind Forecasts, 

Power Systems

Trancoso, Ana Rosa, et al. REN Online Monitoring and 

Prediction of Wind Power: Portuguese Transmission 

System Operator’s Methodology. ENER’06, 28. 

September, 2006. Figueira da Foz.

Portugal

Wind Forecasts, 

Power Systems

Trancoso, Ana Rosa, et al, Wind power predictability: 

comparative study of forecasts with Mesoscale Model 

Version 5 and Weather Research and Forecasting 

Model for Portuguese transmission system operator. 

EMS7/ECAM8 Abstracts, Vol. 4, EMS2007-A-00260, 

20077th EMS Annual Meeting / 8th ECAM, Madrid, Oct 

1-5, 2007.

Portugal Power Systems

Vasconcelos, H., Pecas Lopes, J.A., ANN Design for 

Fast Security Evaluation of Interconnected Systems with 

Large Wind Power Production, Proceedings of PMAPS 

2006, Stockholm, Sweden, June, 2006.

Spain

Wind Integration, 

Power Systems

AEE (Spanish Wind Energy Association). Procedure for 

verification validation and certification of the 

requirements of the PO 12.3 on the response of wind 

farms in the event of voltage dips, (in Spanish and 

English) AEE. 2008. 
IEA Wind Task 24 Final Report, Vol. 1

128

Country/ continent 

(leading author) Topic Reference Link

Spain

Wind-Hydro, 

Energy Markets

Angarita, Jorge Marquez and Usaola, Julio Garcia, 2007. 

Combining hydro-generation and wind energy. Biddings 

and operation on electricity spot markets, Electric Power 

Systems Research, Vol. 77, Issues 5-6, pp. 393-400, 

April, 2007. 

www.sciencedirect.com

Spain

Wind Integration, 

Power Systems

Criado, R., Soto, J., Rodríguez, J. M., Martin, L. 

Fernández, J.L., Molina, J.L., Tapia, A., Saez, J.R. 

Analysis and control strategies of wind energy in the 

Spanish power system. Proc. 2000 CIGRE (Paris).

Spain

Wind Integration, 

Wind Forecasts,

Energy Markets

Fabbri, A.; Roman, T.G.S.; Abbad, J.R.; Quezada, 

V.H.M. Assessment of the Cost Associated With Wind 

Generation Prediction Errors in a Liberalized Electricity 

Market. IEEE Transactions on Power Systems. Vol. 20 

(3), Aug. 2005. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Power Systems

Feijoo, A.E.; Cidras, J.; Dornelas, J.L.G. Wind speed 

simulation in wind farms for steady-state security 

assessment of electrical power systems. IEEE 

Transaction on Energy Conversion, Vol. 14 (4), Dec. 

1999. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Power Systems

Gómez-Lázaro, E., Cañas, M., Fuentes, J.A., Molina A. 

Discussion on the Grid Disturbance on 4 November 2006 

and its effects in a Spanish Wind Farm, Nordic Wind 

Power Conference – NWPC’2007, Roskilde (Denmark), 

November 2007

Spain

Wind Integration, 

Reactive Power, 

Power Systems

Gómez, E., Fuentes, J. A., Molina, A., Ruz, F., Jiménez, 

F., 2006. Results using Different Reactive Power 

Definitions for Wind Turbines Submitted to Voltage Dips: 

Application to the Spanish Grid Code, Power Systems 

Conference, October-November 2006, Atlanta, USA.

Spain

Wind Integration, 

Power Systems

Gómez-Lázaro, E., Cañas, M., Fuentes, J.A., Molina, A., 

Ruz, F., Jiménez, F. Field Measurements on Wind 

Turbines: a Voltage Dip Characterization under the 

Spanish Grid Code. 9th International Conference on 

Electrical Power Quality and Utilisation. Barcelona 

(Spain), October 2007
IEA Wind Task 24 Final Report, Vol. 1

129

Country/ continent 

(leading author) Topic Reference Link

Spain

Wind Integration, 

Power Systems

Gómez, E., Fuentes, J. A., Molina-García, A., Ruz, F., 

Jiménez, F., 2007. Field Tests of Wind Turbines 

Submitted to Real Voltage Dips under the New Spanish 

Grid Code Requirements. Wind Energy, Vol. 10, Issue 5, 

pp 483-295, 2007

Spain Wind Integration

Gómez, E., Fuentes, J. A., Molina-García, A., Ruz, F., 

Jiménez, F., 2007b. Wind Turbine Modeling: Comparison 

of Advanced Tools for Transient Analysis, PES General 

Meeting, June 2007, Tampa, USA. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Power Systems

Ledesma, P.; Usaola, J. Doubly fed induction generator 

model for transient stability analysis. IEEE Transaction 

on Energy Conversion, Vol. 20 (2), pp. 388-397, June 

2005. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Regulation

Morales, A.; Robe, X.; Sala, M.; Prats, P.; Aguerri, C.; 

Torres, E. Advanced grid requirements for the integration 

of wind farms into the Spanish transmission system. IET 

Renewable Power Generation, Vol. 2 (1), March 2008. 

ieeeexplore.ieee.org

Spain Wind Integration

REE 1995, General criteria of Protection of the Electrical 

System Peninsular Spanish, REE and Power 

Companies. 1995.

Spain Wind Integration

Rodríguez, J.M., Alvira, D., Bañares, S. The Spanish 

Experience of the grid integration of wind energy 

sources. IEEE Power Tech 2005. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Power Systems

Rodriguez, J.M.; Fernandez, J.L.; Beato, D.; Iturbe, R.; 

Usaola, J.; Ledesma, P.; Wilhelmi, J.R. Incidence on 

power system dynamics of high penetration of fixed 

speed and doubly fed wind energy systems: study of the 

Spanish case. IEEE Transactions on Power Systems, 

Vol.17(4). Nov. 2002. 

ieeeexplore.ieee.org

Spain Wind Integration

Rodriguez-Bobada, F, Reis Rodriguez, A, Ceña, A, 

Giraut, E, Study of wind energy penetration in the Iberian 

peninsula. European Wind Energy Conference (EWEC), 

27 February – 2 March, 2006, Athens, Greece. 

www.ewec2006proceedings.info/allfiles2/743

_Ewec2006fullpaper.pdf
IEA Wind Task 24 Final Report, Vol. 1

130

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(leading author) Topic Reference Link

Spain Wind Integration

Rodriguez-Garcia, J.M.; Dominguez, T.; Alonso, J. F.; 

Imaz, L. Large integration of wind power: the Spanish 

experience. IEEE Power Engineering Society General 

Meeting, 24-28 June 2007. 

ieeeexplore.ieee.org

Spain Wind Integration

Usaola, J.; Ledesma, P. Dynamic incidence of wind 

turbines in networks with high wind penetration. IEEE 

Power Engineering Society Summer Meeting, Vol. 2, 15-

19 July 2001. 

ieeeexplore.ieee.org

Spain Wind Integration

Usaola, J.; Ledesma, P.; Rodriguez, J.M.; Fernandez, 

J.L.; Beato, D.; Iturbe, R.; Wilhelmi, J.R. Transient 

stability studies in grids with great wind power 

penetration. Modeling issues and operation 

requirements. IEEE Power Engineering Society General 

Meeting, 2003. 

ieeeexplore.ieee.org

Spain

Wind Integration, 

Wind Forecasts

Usaola, Julio, et al. SIPREOLICO, A Wind Power 

Prediction Tool for the Spanish Peninsular Power System 

Operation, in Proceedings from CIGRE 40th General 

Session and Exhibition, 2004.

Sweden Wind Integration

Ackermann, Thomas, 2005. European Wind Power 

Integration Experience, Solar 05 ANZSES, Dunedin, New 

Zealend, 2005.

Sweden

Wind Integration, 

Regulation

Axelsson U, Murray R, Neimane V, 4000 MW wind power 

in Sweden - Impact on regulation and reserve 

requirements. Elforsk Report 05:19, Stockholm, 2005. 

www.elforsk.se

Sweden Wind-Hydro

Jäderström, Anna; Matevosyan, Julija; and Söder, 

Lennart. Coordinated regulation of wind power and hydro 

power with separate ownership, IEWT 05, Vienna, 

Austria, 2005

Sweden Wind Forecasts

Kariniotakis, G., et al, 2006. Next generation forecasting 

tools for the optimal management of wind generation, 

Proceedings PMAPS Conference, 'Probabilistic Methods 

Applied to Power Systems', KTH, Stockholm, Sweden, 

June 2006.
IEA Wind Task 24 Final Report, Vol. 1

131

Country/ continent 

(leading author) Topic Reference Link

Sweden

Wind Integration, 

Wind Forecasts

Lindgren, Elin and Söder, Lennart, 2006. Minimizing 

regulation costs in multi-area systems with uncertain 

wind power forecasts, Nordic Wind Power Conference 

NWPC'2006, Espoo, Finland, 2006

Sweden

Wind Integration, 

Energy Markets

Lindgren, Elin and Söder, Lennart, 2005. Wind Power 

Impact on Costs for Regulating Power in Multi-Area 

Markets, Fifth International Workshop on Large-Scale 

Integration of Wind Power and Transmission Networks 

for Offshore Wind Farms, Glasgow, Scotland, 2005

Sweden Wind Integration

Matevosyan, J., 2006. Wind power integration in power 

system with transmission bottlenecks, PhD study, KTH, 

Sweden, 2006. 

www.divaportal.org/kth/theses/abstract.xsql?dbid=410

8

Sweden Wind-Hydro

Matevosyan, Julija, 2006. On the Coordination of Wind 

and Hydro Power. 6th International Workshop on LargeScale Wind Power Integration, October, 2006

Sweden Wind Integration

Matevosyan, Julija, 2005. Wind Power in Areas with 

Limited Transmission Capacity, Wind Power in Power 

Systems, Wiley & Sons, 2005

Sweden Wind-Hydro

Matevosyan, Julija et al., Hydro Power Planning 

Coordinated with Wind Power in Areas with Congestion 

Problems for Trading on the Spot and the Regulating 

Market.

Sweden

Wind Integration, 

Energy Markets

Matevosyan, Julija and Söder, Lennart, 2006. 

Minimization of imbalance costs trading wind power on 

the short-term power market, IEEE Transactions on 

Power Systems, (no. 3,) pp. 1396-1404, August, 2006. 

ieeeexplore.ieee.org

Sweden Wind-Hydro

Matevosyan, Julija, Söder, Lennart, Optimal daily 

planning for hydro power system coordinated with wind 

power in areas with limited export capability, Proceedings 

Probabilistic Methods Applied to Power Systems 

Conference, 2006
IEA Wind Task 24 Final Report, Vol. 1

132

Country/ continent 

(leading author) Topic Reference Link

Sweden Wind-Hydro

Matevosyan, Julija and Soder, Lennart, 2007. Short-term 

Hydropower Planning Coordinated with Wind Power in 

Areas with Congestion Problems, Wind Energy, February 

2007; 10:195-208. 

www3.interscience.wiley.com/cgibin/fulltext/114113010/PDFSTART

Sweden Wind Integration Neij, L. 1999, Cost Dynamics of Wind Power, Energy 24,

Sweden Wind-Hydro

Ohrvall, F., 2008. Samkorning av vindkraft och 

vattenkraft I Skellefrealven, Elforsk report V-107, 2008. 

(Summary in English) 

www.vindenergi.org

Sweden Wind Integration

Söder, L. 1994. Integration study of small amounts of 

wind power in the power system. Royal Institute of 

Technology KTH report TRITA-EES-9401

Sweden Wind Integration

Söder, Lennart. 2005. Modelling Approach impact on 

estimation of integration cost of wind power, 7th IAEE, 

Bergen, Norway, 2005

Sweden Wind Integration

Söder, Lennart, 2004. On limits for Wind Power 

Generation, Published in International Journal of Global 

Energy Issues, Vol. 21, Issue 3, pp. 243-254, March 

2004

Sweden Wind Integration

Söder, Lennart, 2005. The Value of Wind Power, Wind 

Power in Power Systems, (pp. 169-195,) John Wiley & 

Sons, Ltd, 2005

Sweden Wind Integration

Söder, L.; Ekwue, A.; and Douglas, J. 2006. Study on the 

technical security rules of the European electricity 

network. Royal Institute of Technology (KTH) report 

TRITA-EE 2006:003.

Sweden

Wind Integration, 

Power 

Characteristics

Söder, L, Holttinen, H, 2007. On methodology for 

modeling power system impact of wind power. Int. J.of 

Global Energy Issues, Vol 25, 2007 (in print).

Sweden Wind Integration

Söder, L, Hofmann, L, Nielsen, C S, Holttinen, H, 2006. 

Experience from wind integration in some high 

penetration areas. Nordic Wind Power Conference, 22-

23 May, 2006, Espoo, Finland. VTT, Espoo, 2006.
IEA Wind Task 24 Final Report, Vol. 1

133

Country/ continent 

(leading author) Topic Reference Link

United Kingdom

Wind Integration, 

Wind-Hydro

Bathurst, G.N. and Strbac, G. 2003. Value of Combining 

Energy Storage and Wind in Short-Term Energy and 

Balancing Markets, Electric Power Systems Research, 

67, pp. 1-8. January. 

www.elsevier.com/locate/epsr

United Kingdom Wind Integration

Dale, Milborrow D, Slark, & Strbac G, 2003. A shift to 

wind is not unfeasible (Total Cost Estimates for Largescale Wind Scenarios in UK). Power UK Journal Issue 

109, 17-25. 

www.bwea.com/pdf/PowerUK-March2003-

page17-25.pdf

United Kingdom

Wind Integration, 

Power 

Characteristics

DTI Centre for Distributed Generation and Sustainable 

Electrical Energy, Influence of wind farms on power 

system dynamic and transient stability, Summary Report 

to ESTISG (www.dti.gov.uk), February 2005.

United Kingdom Wind Integration

Gross, Robert et al. 2006. The Costs and Impacts of 

Intermittency: An assessment of the evidence on the 

costs and impacts of intermittent generation on the 

British electricity network. UKERC

United Kingdom Literature Survey

MacDonald M, 2003. The Carbon Trust & DTI 

Renewables Network Impact Study Annex 4: 

Intermittency Literature Survey & Roadmap. 2003. The 

Carbon Trust & DTI. 2003. 

United Kingdom Wind Integration

Milborrow D, 2005. Capacity credit of renewable energy 

sources in the UK, Report to ESTISG, Feb. 2005.

United Kingdom Wind Integration

Royal Academy of Engineering & PB Power. The Cost of 

Generating Electricity. 2004. 

www.raeng.org.uk/news/publications/list/repo

rts/Cost_of_Generating_Electricity.pdf

United Kingdom

Wind Integration, 

Wind-Hydro

Strbac G, Black M, Value of storage in managing 

intermittency, Report to DTI (www.sedg.ac.uk), May 

2004.

United Kingdom

Wind Integration, 

Power 

Characteristics

Strbac G, Bopp T, Value of fault ride through capability 

for wind farms, Report to Ofgem (www.sedg.ac.uk), July 

2004. 

www.sedg.ac.uk
IEA Wind Task 24 Final Report, Vol. 1

134

Country/ continent 

(leading author) Topic Reference Link

United Kingdom Wind Integration

Strbac, Goran, Shakoor, Anser, Black, Mary, Pudjianto, 

David, Bopp, Thomas, 2007. Impact of wind generation 

on the operation and development of the UK electricity 

systems, Electrical Power Systems Research, Volume 

77, Issue 9, Pages 1143-1238, Elsevier 2007. 

www.sciencedirect.com/science?_ob=Article

URL&_udi=B6V30-4M4KK9Y1&_user=10&_rdoc=1&_fmt=&_orig=search&

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on=1&_urlVersion=0&_userid=10&md5=45ff

1a312ff87c918f895d13daa7249c

United States Wind Integration

Acker, T., 2007, Final Report: Arizona Public Service 

Wind Integration Cost Impact Study, Northern Arizona 

University, October 2007.

wind.nau.edu/APSWindIntegrationsStudy.sht

ml

United States

Wind Integration, 

Wind-Hydro

Acker, T., Buechler, J., Knitter, K., and Conway, K., 

2007, Impacts Of Integrating Wind Power Into The Grant 

County PUD Balancing Area, Proceedings of the AWEA 

Windpower 2007 Conference, Los Angeles, CA, June.

United States

Wind Integration, 

Wind-Hydro

Acker, T., 2007, IEA Task 24: Integration Wind and 

Hydropower Systems, Proceedings of the 2006 Global 

Wind Power Conference, Adelaide, Australia, 

September.

United States

Wind Integration, 

Wind-Hydro

Acker, T., Knitter, K., Conway, K., and Buechler, J., 

2006, Integrating Wind and Hydropower on the MidColumbia River in Grant County, Washington, 

Proceedings of the AWEA Windpower 2006 Conference, 

Pittsburghh, PA, June.

United States

Wind Integration, 

Wind-Hydro

Acker, T., Knitter, K., Conway, K., and Buechler, J., 

2006, Wind and Hydropower Integration in the Grant 

County Public Utility District, Washington, Proceedings of 

the Hydrovision 2006 Conference, Portland, OR, August.

United States

Wind Integration, 

Wind-Hydro

Acker, T., 2005, Synthesizing Wind and Hydropower: 

Opportunities and Challenges, Proceedings of the 

Waterpower XIV Conference, Austin, TX, July.

United States

Wind Integration, 

Wind-Hydro

Acker, T., 2005, Characterization of Wind and 

Hydropower Integration in the USA, Proceedings of the 

AWEA Windpower 2005 Conference, Denver, CO, May.
IEA Wind Task 24 Final Report, Vol. 1

135

Country/ continent 

(leading author) Topic Reference Link

United States

Wind Integration, 

Wind-Hydro

Acker, T. and Parson, B., 2004, Opportunities to 

Optimize Hydropower and Wind Energy Systems 

Through Coordination, Cooperation, or Integration,

Proceedings of the Global Windpower Conference, 

Chicago, IL, March.

United States Wind-Hydro

Ancona, Daniel and Krau, Stéphane et.al. 2003. 

Operational Constraints and Economic Benefits of WindHydro Hybrid Systems – Analysis of Systems in the 

U.S./Canada and Russia, Princeton Energy Resources 

International, LLC, European Wind Energy Conference, 

Madrid, Spain, June. 

www.perihq.com/archives.htm

United States Wind Forecasts

AWS Scientific and Truewind Solutions, 2003. Overview 

of Wind Energy Generation Forecasting. Submitted to 

NYSERDA and NYISO. 

www.uwig.org/forecst_overview_report_dec_

2003.pdf

United States Wind Integration

Bai, Xiggang, 2007. Intermittency Analysis Project, 

Appendix B: Impact of Intermittent Generation on 

Operation of California Power Grid, California Energy 

Commission. 

United States Wind Forecasts

Bailey, Bruce, 2007. PIER Project Task Report: 

California Wind Energy Resource Modeling and 

Measurement, Measurement Program Final Report. 

United States Wind Forecasts

Banta, R.M., 2003, Analysis of Cases-99, LIDAR and 

Turbulence Data in Support of Wind Turbine Effects, 

NREL. 

www.osti.gov/bridge

United States Wind Forecasts

Bielecki, M., et al. (2010). Characterization of Errors in 

Wind Power Forecasting, Master’s Thesis, Northern 

Arizona University, 2010. 

www.nau.edu/library

United States

Wind Integration, 

Energy Markets

Bird, L., Parsons, B., Gagliano, T., and Brown, M., Wiser 

R., Bolinger, M., 2003. Policies and Market Factors 

Driving Wind Power Development in the United States. 

NREL/TP-620-34599, National Renewable Energy 

Laboratory, Colorado, US.

United States Wind-Hydro

Bonneville Power Administration- Integration of Wind with 

Hydro-electric Generation
IEA Wind Task 24 Final Report, Vol. 1

136

Country/ continent 

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United States Wind Integration

Brooks, Daniel et al. Assessing the Impact of Wind 

Generation at System Operations at XCEL Energy -

North and Bonneville Power Administration. 

www.uwig.org/operatingimpacts.html

United States Wind Integration

Brooks, Daniel et al. 2003 Characterizing the Impacts of 

Significant Wind Generation Facilities on Bulk Power 

System Operations Planning, XCEL Energy - North Case 

Study. 

www.uwig.org/operatingimpacts.html

United States Wind Integration

Brower, Michael, 2007, Intermittency Analysis Project: 

Characterizing New Wind Resources in California, 

California Energy Commission. 

www.energy.ca.gov/pier/notices/2007-02-

13_workshop/presentations/05_2007-02-

13_YEN+AWS.PDF

United States

Wind Integration, 

Wind-Hydro

Buechler, Jason and Acker, Tom, 2008. Grant County 

Public Utility District Wind Integration Study. (still in edit)

United States Wind Integration

Cadogan, J. and Milligan, M. et.al. 2000. Short-Term

Output Variations in Wind Farms—Implications for 

Ancillary Services in the United States, NREL/CP-500-

29155, National Renewable Energy Laboratory, Golden, 

CO, September. 

www.nrel.gov/publications

United States Wind Integration

California Independent System Operator. Integration of 

Renewable Resources: Transmission and operating 

issues and recommendations for integrating renewable 

resources on the California ISO-controlled grid. 

November, 2007

United States Wind Integration

California Wind Energy Collaborative, 2006, Impact of 

Past, Present and Future Wind Turbine Technologies on 

Transmission System Operation and Performance, 

California Energy Commission.

United States Wind Integration

Cardinal and Miller, 2006. Grid Friendly Wind Plant 

Controls: WindCONTROL – Field Test Results, 

WindPower 2006, Pittsburghh, PA, US

United States Wind-Hydro

Cheng, Edmond 1989. An Investigation of a Pumped 

Storage Hydropower System. Waterpower, 1989.
IEA Wind Task 24 Final Report, Vol. 1

137

Country/ continent 

(leading author) Topic Reference Link

United States Wind-Hydro

Cohen, Joseph and Lafrance, Gaetan et.al. 2003. 

Analysis of Wind-Hydro Integration Value In Vermont, 

Windpower 2003, Hybrid And Distributed Generation 

Session, Princeton Energy Resources International, LLC, 

May.

United States Wind Integration

Davis, Ronald, 2007 Intermittency Analysis Project, 

Appendix A: Intermittency Impacts of Wind and Solar 

Resources on Transmission Reliability, California Energy 

Commission. 

United States Wind Integration

DeMeo E A, Grant W, Milligan M, Schuerger M J, Wind 

plant integration: costs, status and issues, IEEE power & 

energy magazine, nov/dec 2005.

United States Wind Integration

Department of Energy, 2008. 20% Wind Energy by 2030. 

Increasing Wind Energy's Contribution to the US Electric 

Supply.

www.20percentwind.org/20percent_wind_en

ergy_report_revOct08.pdf

United States Power Systems

Dragoon, K. and Dvortsov, V. 2006. Z-Method for Power 

System Resource Adequacy Applications. IEEE 

Transactions on Power Systems, Vol. 21, No.2, May 

2006. 

ieeeexplore.ieee.org

United States Wind Integration

Dragoon, K. and Milligan, M. 2003. Assessing Wind 

Integration Costs with Dispatch Models: A Case Study of 

PacifiCorp, NREL/CP-500-34022, National Renewable 

Energy Laboratory, Golden, CO. May.

United States

Wind Integration, 

Wind-Hydro

EnerNex Corporation, 2007. Avista Corporation Wind 

Integration Study Final Report. March, 2007. 

www.avistautilities.com/inside/resources/irp/e

lectric/Documents/AvistaWindIntegrationStud

y.pdf

United States

Wind Integration, 

Systems Analysis

Electrotek Concepts, Systems Operations Impacts of 

Wind Generation Integration Study. Prepared for We 

Energies, June 2003. 

www.uwig.org/WeEnergiesWindImpacts_Fin

alReport.pdf

United States

Wind Integration, 

Wind Forecasts

EnerNex Corporation and Wind Logics, Inc. 2004. 

Characterization of the Wind Resource in the Upper 

Midwest Wind Integration Study – Task 1, Xcel Energy 

and the Minnesota Department of Commerce, Knoxville, 

TN, September. 

www.enernex.com/staff/publications.htm
IEA Wind Task 24 Final Report, Vol. 1

138

Country/ continent 

(leading author) Topic Reference Link

United States

Wind Integration, 

Wind-Hydro

EnerNex Corporation and Wind Logics, 2004. Wind 

Integration Study – Final Report. Xcel Energy and the 

Minnesota Department of Commerce, Knoxville, TN, 

September. 

www.enernex.com/staff/downreports.htm

United States Wind Integration

EnerNex Corporation and Idaho Power Company, 2007. 

Operational Impacts of Integrating Wind Generation into 

Idaho Power's Existing Resource Portfolio. 

www.enernex.com

United States Wind Integration

ERCOT, 2007. ERCOT Operations Report on the EECP

event on February 8, 2007. 

www.ercot.com/meetings/ros/keydocs/2007/0

315/07._ERCOT_OPERATIONS_REPORT_

EECP020807_rev3.doc

(download link)

United States Wind Integration

GE Energy, 2004. The Effects of Integrating Wind Power 

On Transmission System Planning, Reliability, and 

Operations, Report on Phase 1: Preliminary Overall 

Reliability Assessment, Prepared for the New York State 

Energy Research and Development Authority, by 

General Electric’s Power Systems Energy Consulting, 

Schenectady, NY.

www.uwig.org/phase%20_1_feb_02_04.pdf

United States Wind Integration

GE Energy, 2005. The Effects of Integrating Wind Power 

on Transmission System Planning, Reliability, and 

Operations: Report on Phase 2, Prepared for The New 

York State Energy Research and Development Authority, 

City, State, Mar. 2005. 

www.nyserda.org/publications/wind_integrati

on_report.pdf

United States Wind Forecasts

Hand, N.M., Kelly, N.D., Balas, M.J. 2003, Identification 

of Wind Turbine Response to Turbulent Inflow 

Structures, NREL.

United States Wind Forecasts

Hand, N.M., Maureen, M. 2003, Mitigation of Wind 

Turbine/Vortex Interaction Using Disturbance 

Accommodating Control, NREL. 

www.osti.gov/bridge

United States Wind-Hydro

Hanson, R.J., Millham, C.B., Estimating the Costs in Lost 

Power of Alternative Snake-Columbia Basin 

Management Policies. Water Resources Research, Vol. 

17, No. 5, pp. 1295-1303, October 1981.
IEA Wind Task 24 Final Report, Vol. 1

139

Country/ continent 

(leading author) Topic Reference Link

United States Wind Forecasts

Harris, M., Hand, M, and Wright, M. 2005, LIDAR for 

Turbine Control, NREL. www.osti.gov/bridge

United States

Wind Integration, 

Wind-Hydro

Hirst, Eric 2002. Integrating Wind Energy With The BPA 

Power System: Preliminary Study, Consultant, Oak 

Ridge, TN, September. 

www.bpa.gov/Power/pgc/wind/Wind_Integrati

on_Study_09-2002.pdf

United States Wind-Hydro

Hirst, Eric 2003. The Value of Regulation and Spinning 

Reserves for Hydroelectric Resources. 

United States Wind Integration

Hirst, Eric and Kirby, Brendan 2003. Allocating Costs of 

Ancillary Services: Contingency Reserves and 

Regulation, ORNL/TM-2003/152, Oak Ridge National 

Laboratory, Oak Ridge, TN, June. 

United States Load Analysis

Hirst, Eric and Kirby, Brendan. Defining Intra-And 

Interhour Load Swings, Oak Ridge National Laboratory, 

Oak Ridge, TN. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Hirst, Eric and Kirby, Brendan 2001. Measuring 

Generator Performance In Providing Regulation And 

Load-Following Ancillary Services, ORNL/TM-2000/383, 

Oak Ridge National Laboratory, Oak Ridge, TN, January. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Hirst, Eric and Kirby, Brendan 2000. What Is The Correct 

Time-Averaging Period For The Regulation Ancillary 

Service?, Oak Ridge National Laboratory, Oak Ridge, 

TN, April. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Hirst, Eric and Kirby, Brendan 2001. Measuring 

Generator Performance In Providing Regulation And 

Load-Following Ancillary Services, ORNL/TM-2000/383, 

Oak Ridge National Laboratory, Oak Ridge, TN, January. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Hirst, Eric and Kirby, Brendan 1996. Electric-Power 

Ancillary Services, ORNL/CON-426, Oak Ridge National 

Laboratory, Oak Ridge, TN, February. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd

/fqma/tpsext/SF

United States Wind Integration

Hudson, Randy and Kirby, Brendan and Wan, Yih-Huei. 

Regulation Requirements For Wind Generation Facilities, 

Oak Ridge National Laboratory, Oak Ridge, TN and 

National Renewable Energy Laboratory, Golden, CO. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF
IEA Wind Task 24 Final Report, Vol. 1

140

Country/ continent 

(leading author) Topic Reference Link

United States

Wind Integration, 

Coal

Ihle, J, Owens, B. 2004, Integrated Coal and Wind Power 

Development in the U.S. Upper Great Plains.

United States Wind Forecasts

Jaynes, Daniel et al. 2007, MTC Final Progress Report: 

LIDAR, NREL. www.osti.gov/bridge

United States Wind Forecasts

Kelley, N.D., et al. 2007, Comparing Pulsed Doppler 

LIDAR with SODAR and Direct Measurements for Wind 

Assessment, NREL. 

www.osti.gov/bridge

United States Wind Integration

Kirby, Brendan 2003. Spinning Reserve From 

Responsive Loads, ORNL/TM-2003/19, Oak Ridge 

National Laboratory, Oak Ridge, TN, March. 

www.osti.gov/bridge

United States Wind Integration

Kirby, Brendan and Hirst, Eric 2000. Customer-Specific 

Metrics For The Regulation And Load-Following Ancillary 

Services, ORNL/CON-474, Oak Ridge National 

Laboratory, Oak Ridge, TN, January. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Kirby, Brendan and Hirst, Eric 2000. Pricing Ancillary 

Services So Customers Pay For What They Use, Oak 

Ridge National Laboratory, Oak Ridge, TN. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd/

fqma/tpsext/SF

United States Wind Integration

Kirby, Brendan and Hirst, Eric 2001. Using Five-Minute 

Data To Allocate Load-Following And Regulation 

Requirements Among Individual Customers, ORNL/TM2001/13, Oak Ridge National Laboratory, Oak Ridge, TN, 

January. 

lib1.isd.ornl.gov:8182/TSEARCH/BASIS/tidd

/fqma/tpsext/SF

United States Wind Integration

Kirby, Brendan and Milligan, Michael. A Method and 

Case Study for Estimating The Ramping Capability of a 

Control Area or Balancing Authority and Implications for 

Moderate or High Wind Penetration, Oak Ridge National 

Laboratory, Oak Ridge, TN. 

www.nrel.gov/publications

United States Wind Integration

Komer, P. Wind Power: Opportunity or Albatross, Platts 

Research and Consulting.

United States Wind Integration

Krich, A. and Milligan, M. 2005. The Impact of Wind 

Energy on Hourly Load Following Requirements: An 

Hourly and Seasonal Analysis, NREL/CP-500-38061, 

National Renewable Energy Laboratory, Golden, CO, 

May. 

www.nrel.gov/publications
IEA Wind Task 24 Final Report, Vol. 1

141

Country/ continent 

(leading author) Topic Reference Link

United States Wind Forecasts

Lackner, M.A. et al. 2007. The Round Robin Site 

Assessment Method: A New Approach to Wind Energy 

Site Assessment. Renewable Energy, Vol. 33 (2008), pp. 

2019-2026. 

www.sciencedirect.com or www.elsevier.com

United States Wind Integration

McGill, Chris. 2005, Wind Energy and Natural Gas: 

Balancing Price and Supply Volatility, National Wind 

Coordinating Committee.

www.aceny.org/pdfs/wind_facts/aga_on_win

d.pdf

United States Wind-Hydro

Millham, C.B. 1985. Using Hydropower to Smooth 

Intermittent and Unreliable Sources of Generation, 

Washington State University, Pullman, WA. May. Applied 

Mathematical Modelling. Vol. 9, no. 5, pp. 314-320. 1985

United States Wind Integration

Milligan, M. and Porter, K. 2005. Determining the 

Capacity Value of Wind: A Survey of Methods and 

Implementation, NREL/CP-500-38062, National 

Renewable Energy Laboratory, Golden, CO, May. 

www.nrel.gov/publications

United States Wind Integration

Milligan, Michael 2002. Modeling Utility-Scale Wind 

Power Plants Part 2: Capacity Credit, NREL/TP-500-

29701, National Renewable Energy Laboratory, Golden, 

CO, March. 

www.nrel.gov/publications

United States Wind Integration

Milligan, Michael and Parsons, Brian 1997. A 

Comparison and Case Study of Capacity Credit 

Algorithms for Intermittent Generators, NREL/CP-440-

22591, National Renewable Energy Laboratory, Golden, 

CO, April. 

www.nrel.gov/publications

United States Wind Integration

Milligan, M, 2003. Wind power plants and system 

operation in the hourly time domain. Proceedings of 

Windpower 2003 conference, May 18–21, 2003 Austin, 

Texas, USA. NREL/CP-500-33955. 

www.nrel.gov/publications

United States Wind Forecasts

Milligan, M. and Schwartz, M.N. et.al. 2003. Statistical 

Wind Power Forecasting for U.S. Wind Farms, 

NREL/CP-500-35087, National Renewable Energy 

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United States Wind Integration

Milligan, M. Measuring Wind Plant Capacity Value. 

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United States Wind Integration

Milligan, M, Porter, K, 2005. The Capacity Value of Wind 

in the United States: Methods and Implementation.

Electricity Journal, Vol. 19, Issue 2, March 2006. pp 91-

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United States Wind Forecasts

Moore, Kathleen and Bailey, Bruce, 2002. SODAR for 

Wind Energy Resource Assessment. American Wind 

Energy Association

United States

Reactive Power, 

Wind Integration

Mulijadi, E. and Butterfield, C.P. and Yinger, R. and 

Romanowitz, H. 2004. Energy Storage and Reactive 

Power Compensator in a Large Wind Farm, National 

Renewable Energy Laboratory, Golden, CO. January. www.nrel.gov/publications

United States Wind Integration Northwest Wind Integration Action Plan, 2007. www.nwcouncil.org/energy/Wind/Default.asp

United States Wind Integration

New York - General Electric, NYSERDA Phase 2 

Appendices

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United States Wind Integration Pacificorp, 2007. Integrated Resource Plan. 

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United States

Wind Integration, 

Grid System

Parsons, B. et al. 2003, Grid Impacts of Wind Power: A 

Summary of Recent Studies in the United States. 

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United States

Wind-Hydro 

Integration

Pete, C., (2010). Implications on hydropower from largescale integration of wind and solar power in the West: 

results from the Western Wind and Solar Integration 

Study, Thesis Report, Northern Arizona University 

Mechanical Engineering Department, 2010. 

Available from the cline library 

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United States Wind Integration

Piwko, R., Clark, K., Freeman, L., Jordan, G., Miller, N., 

(2010). Western Wind and Solar Integration Study, NREL 

Subcontract Report, 2010. 

United States Wind Integration

Porter, Kevin. 2007. PIER Project Report: Review of 

International Experience Integrating Variable Renewable 

Energy Generation, California Energy Commission. 

United States Wind Integration

Porter, Kevin. 2007. PIER Project Report: Review of 

International Experience Integrating Variable Renewable 

Energy Generation: Appendix A Denmark, California 

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IEA Wind Task 24 Final Report, Vol. 1

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United States Wind Integration

Porter, Kevin. 2007. PIER Project Report: Review of 

International Experience Integrating Variable Renewable 

Energy Generation: Appendix B Germany, California 

Energy Commission.

United States Wind Integration

Porter, Kevin. 2007. PIER Project Report: Review of 

International Experience Integrating Variable Renewable 

Energy Generation: Appendix C India, California Energy 

Commission. 

United States Wind Integration

Porter, Kevin. 2007. PIER Project Report: Review of 

International Experience Integrating Variable Renewable 

Energy Generation: Appendix D Spain, California Energy 

Commission. 

United States Wind Integration

Porter, Kevin. 2007. Intermittency Analysis Project: Final 

Report. California Energy Commission, Public Interest 

Energy Research Program. July, 2007. 

United States

Wind Integration, 

Wind Forecasts

Potter, Cameron et al. 2008. Creating the Dataset for the 

Western Wind and Solar Integration Study (U.S.A.). 7th 

International Workshop on Large Scale Integration of 

Wind Power and Transmission Networks for Offshore 

Wind Farms.

United States Wind Forecasts

Ray, M.L. et al. 2006, Analysis of Wind Shear Models 

and Trends in Different Terrains, University of 

Massachusetts. 

United States Wind Integration

Shiu, H., Milligan, M., Kirby, B. Jackson, K., 2006. 

California Renewables Portfolio Standard Renewable 

Generation Integration Cost Analysis. California Energy 

Commission, PIER Public Interest Energy Research 

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United States Wind Integration

Short, W., and Sullivan, P. 2007, Modeling the National 

Potential for Offshore Wind, Preprint, NREL. 
IEA Wind Task 24 Final Report, Vol. 1

144

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United States Wind Integration

Smith, Charles and DeMeo, Edgar et.al. 2004. Wind 

Power Impacts On Electric Power System Operating 

Costs: Summary And Perspective On Work To Date, 

American Wind Energy Association Global WindPower 

Conference, Chicago, IL, March. 

www.uwig.org

United States Wind Integration

Smith, J. C., Milligan, M.R., DeMeo, E.A., Parsons, B. 

Utility Wind Integration and Operating Impact State of the 

Art. IEEE TRANSACTIONS ON POWER SYSTEMS, 

VOL. 22, NO. 3, AUGUST 2007. 

United States Wind Integration

Smith, J.C, Parsons, B., Acker, T., Milligan, M., Zavadil, 

R., Schuerger, M., and DeMeo, E., 2007, Best Practices 

in Grid Integration of Variable Wind Power: Summary of 

Recent US Case Study Results and Mitigation Measures,

Proceedings of the 2007 European Wind Energy 

Conference, Milan, Italy, May.

United States Wind-Hydro

TrueWind Solutions and AWS Scientific, 2003. Overview 

of Wind Energy Generation Forecasting. Draft Report. 

New York State Energy and Research Development 

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United States Wind Integration

Walling, Reigh. Analysis of Wind Generation Impact on 

ERCOT Ancillary Services Requirements; GE, March, 

2008. 

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United States Wind Integration

Wan, Y, 2005. Fluctuation and Ramping Characteristics 

of Large Wind Power Plants. Windpower 2005 

(Windpower 05) Conference and Exhibition (CD-ROM), 

15-18 May 2005, Denver, Colorado. Washington, DC: 

American Wind Energy Association; Content 

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38057.

United States

Wind Integration, 

Systems Analysis

Wan, Y. and Liao, J.R. 2005. Analyses of Wind Energy 

Impact on WFEC System Operations, NREL/TP-500-

37851, National Renewable Energy Laboratory, Golden, 

CO, August. 

www.nrel.gov/publications
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United States Wind Integration

Wan, Y. 2005. Primer on Wind Power for Utility 

Applications. NREL Report No. TP-500-36230. www.nrel.gov/publications

United States Wind Integration

Wan, Y. 2004, Wind Power Plant Behaviors: Analyses of 

Long-Term Wind Power Data, NREL. www.osti.gov/bridge

United States Wind-Hydro

Westrick, Kenneth and Storck, Pascal and Froese, Gerry. 

Reliance on Renewables - The Synergistic Relationship 

between Wind and Hydro Power, American Wind Energy 

Association, 2002. 

www.awea.org/publications

United States Wind Integration

Wiser, Ryan and Bolinger, Mark, Annual Report on U.S. 

Wind Power Installation, Cost, and Performance Trends: 

2006, U.S. DOE Energy Efficiency and Renewable 

Energy. 

United States Wind Integration

Wolf, K. Wind Integration Study Introduction, Minnesota 

Department of Commerce.

United States

Wind Integration, 

Forecasting

Zack, J. 2003, Overview of Wind Energy Generation 

Forecasting, NYSERDA, TrueWind Solutions. 

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ning/special_studies/forecst_overview_report

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United States Wind Integration

Zavadil, R.M. 2003. Wind Generation Technical 

Characteristics for the NYSERDA Wind Impacts Study, 

EnerNex Corporation, Knoxville, TN, November.

United States Wind Integration

Zavadil, R, 2006. Wind Integration Study for Public 

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www.xcelenergy.com/XLWEB/CDA/0,3080,1-

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United States

Wind Integration, 

Wind-Hydro

Zavadil, R.M. 2006. WAPA Wind Integration Study, 

EnerNex Corporation, Knoxville, TN. August. 

www.enernex.com/staff/publications.htm