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Contract No. DE-AC36-08GO28308

The Impact of High Wind Power 

Penetrations on Hydroelectric 

Unit Operations in the WWSIS

Bri-Mathias Hodge, Debra Lew, and 

Michael Milligan

Technical Report

NREL/TP-5500-52251

July 2011
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Contract No. DE-AC36-08GO28308

The Impact of High Wind Power 

Penetrations on Hydroelectric 

Unit Operations in the WWSIS

Bri-Mathias Hodge, Debra Lew, and 

Michael Milligan

Prepared under Task No. WE110810

Technical Report

NREL/TP-5500-52251

July 2011
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1

Abstract — The Western Wind and Solar Integration Study 

(WWSIS) investigated the operational impacts of very high levels 

of variable generation penetration rates (up to 35% by energy) in 

the western United States. This report examines the impact of 

this large amount of wind penetration on hydroelectric unit 

operations. Changes in hydroelectric unit operating patterns are 

examined both for an aggregation of all hydro generators and for 

select individual plants. The cost impacts of maintaining hydro 

unit flexibility are assessed and compared for a number of 

different modes of system operation.

Index Terms— power systems, wind power generation, 

hydroelectric power generation, stochastic systems

I. INTRODUCTION

he growing amounts of variable generation (VG), 

chiefly wind and solar power, being integrated into 

the electricity system are already starting to change 

system operations. As the penetration rates of these 

technologies increase even more, significant changes in 

system operations are expected. The Western Wind and 

Solar Integration Study [1] (WWSIS) investigated the 

operational impacts of very high levels of VG

penetration rates (up to 35% by energy) in a portion of 

the western interconnection of the United States. In the 

most extreme scenarios, 30% of energy in the 

WestConnect footprint was supplied by wind power, 

with an additional 5% split between concentrating solar 

thermal (CSP) and solar photovoltaic (PV) generators. 

While the WestConnect area was the focus of the study, 

the entire U.S. portion of WECC was modeled due to the 

interconnected nature. The details of the WestConnect 

and WECC boundaries can be seen in Figure 1. 

WWSIS studied system operations in the year 2017, 

based on expected system loads, generation unit

retirements and expansions, and transmission build-out. 

While such high levels of VG penetration are not 

expected by 2017, the choice of this year allows for 

reasonable assumptions about the rest of the system, and 

most importantly the transmission grid, to be made 

without requiring long-term forecasting of system 

changes. In order to capture the operational effects of 

this influx of VG, a transmission-constrained hourly 

production cost model (GE MAPS) was used in 

modeling the WECC area. Because there can be large 

differences in operations on an inter-annual basis, the 

system was modeled three times, utilizing timesynchronized load, wind, and solar data from the years 

2004, 2005, and 2006. Because there are not currently 

as many wind and solar sites in WECC as were modeled 

in the study, wind and solar power output time-series

data had to be simulated using a numerical weather 

prediction (NWP) model [2]. Though the goal of the 

study was to model a system close to current system 

operations, some simplifying assumptions were made. 

The most important of these was using only five regional 

balancing areas in the study, instead of the 37 that 

existed in WECC at the start of the study. Balancing 

area consolidation has long been a trend in the United 

States electricity system, and has also been proposed as a 

change in system operations that would be helpful in 

integrating additional amounts of VG [3], though this 

degree of consolidation is not anticipated in the near 

future. The transmission system was reduced to 20 

transmission zones with only inter-zonal interfaces

modeled. It was assumed that there were no 

transmission limits for transfers within each of the 

transmission zones. Additionally, the $9.50/MBTU 

price for natural gas used in the study means that new 

VG primarily displaces gas-fired generators, with the 

consequence that coal plants accommodate much of the 

variability of wind and solar production. 

Figure 1 − Map of the WWSIS footprint including WestConnect 

and WECC boundaries [1]. 

The Impact of High Wind Power Penetrations 

on Hydroelectric Unit Operations in the WWSIS

Bri-Mathias Hodge, Debra Lew, and Michael Milligan

T
2

In this report, we examine how the high wind 

penetration levels modeled in WWSIS impact 

hydroelectric unit operations. Hydroelectric power is 

often seen as the perfect complement to wind power 

because hydro units are quick-starting with high ramping 

rates and, therefore, can balance variations in wind 

power output. However, the reality is not quite as 

simple due to non-power constraints on hydro units. 

Since hydroelectric units often have water use 

constraints, they may be required or prevented from 

operating at certain times to maintain reservoir levels, or 

required to produce in order to avoid spilling that would 

cause exceeding environmental limits on dissolved 

gases. 

Belanger and Gagnon examined the effects of using a 

hydroelectric plant as a backup system to balance the 

variability of a single wind plant [4]. While they chose a

system with large amounts of hydro power generation, 

specifically Quebec, Canada, they did not look at the 

system-wide effects on all hydro generators, and instead 

chose to focus on a single hydro plant. Unsurprisingly, 

they found that the output of the hydroelectric plant was 

significantly different when used exclusively to balance 

the output of a single wind plant, and that this had a 

significant impact on river levels at different times of the 

year. A number of other studies have also examined 

combined wind-hydro systems, usually on small island 

systems where close to one-to-one backup of wind 

power is necessary because of the paucity of other 

generators [5, 6]. However, one must be careful about 

extrapolating these results to larger systems because

wind power does not require one-to-one backup in larger 

systems. Instead, balancing the reduced variability of a 

number of different wind plants together with the 

variability of load is a more efficient approach [7]. One 

study that considers a larger system is Benitez et al. [8]. 

This study looked at using an aggregation of a number of 

hydropower plants to balance wind power in two 

different high wind scenarios for Alberta, Canada. 

Specific concerns addressed were the need for new 

thermal generation, the costs of wind integration, and the 

costs of reducing CO2 emissions. Bueno and Carta [6] 

is also significant because it suggests the use of pumped 

hydro storage as a means of dealing with wind power 

variability, a topic of interest in a number of other 

studies [8-10]. 

The remainder of the report is organized as follows. 

In Section II, the methods and data used in this study are 

described in detail. Section III contains the results of

WWSIS, specifically with regard to the effects of high 

wind power penetration on hydroelectric unit operations. 

Conclusions are then drawn and future areas for 

examination outlined in Section IV.

II. WWSIS METHODS AND DATA

In this section, we describe some of the important

details of the methods and data utilized in the study. 

Section II-A contains information on the various 

scenarios run in WWSIS, in terms of wind penetration 

rates and wind plant locations. Section II-B provides 

details on how the hydroelectric units were modeled

within the production cost simulation model. 

A. Scenarios

The wind resources available in the Western 

Interconnection can vary widely in quality from location 

to location. The choice of where to site the proposed 

wind plants that would combine to meet the study’s 

renewable penetration goals is influenced by many 

factors such as: the quality of local resources, local siting 

and political factors, and transmission capacity 

availability and cost. For this reason, three different 

siting scenarios were devised: the In-Area, Mega Project, 

and Local Priority scenarios. The In-Area scenario 

forced the areas within WestConnect to fulfill their 

renewable goals with local resources located in their area 

of responsibility. The Mega Project scenario selected 

the best quality resources within the total footprint, and 

then built transmission between the areas so that the 

whole footprint met its renewable goal. The Local 

Priority scenario is a combination of the other two 

scenarios that mixes some inter-area transmission 

building with a focus on providing substantial amounts 

of generation locally. One of the more surprising results 

of the WWSIS was that the scenarios chosen had 

relatively minor impacts on the system at the operational 

level. This result is believed to be heavily influenced by 

the choice of using only five balancing areas, and would 

likely change if all of the current balancing areas were 

modeled individually. For this reason, we will focus 

mainly on the In-Area scenario in our analysis of the 

effect of high wind power penetration on hydro 

generator operations.

Though a goal of WWSIS was to examine the impact 

of VG penetration rates above 30% on electricity system 

operations, the changes that would occur in the system at 

lower penetration rates on the trajectory to 30% are also 

important. For this reason, four penetration rate 

scenarios were included in the study. The lowest 

penetration rate case examined the impact of 10% wind 

energy and 1% solar energy in both the WestConnect 

area and the rest of WECC. There were two 20% cases 

created. One examined 20% wind energy and 3% solar 

energy penetration in both WestConnect and WECC as a 

whole. The other included only 10% wind energy and 

1% solar energy in the rest of WECC, while keeping 
3

WestConnect at 20% and 3% for wind and solar energy 

penetration respectively. The final case examined 

penetration rates of 30% wind energy and 5% solar 

energy for WestConnect, with the balance of WECC 

having a 20%/3% split. In our analysis of the impacts on 

hydro generators, we will continually use the different 

penetration cases to examine the impact of increasing 

VG penetration. 

B. Hydroelectric Generation Modeling 

Unlike the wind and solar data used in the WWSIS, 

the hydroelectric modeling does not use time series data

specific to the climate patterns of 2004-2006. Since 

hydro units are dispatchable and can be used to balance 

wind power variability, modeling their operation solely 

on a historical dataset would have increased the

perceived integration cost by neglecting the hydro unit 

flexibility. Instead, each plant was assigned monthly 

energy and plant capacity limits based on 11- year 

averages of these generator-specific variables. This 

allowed the production cost model to dispatch the hydro 

resources subject to their monthly constraints. One 

limitation of this approach is that it always assumes that 

the full hydro generator nameplate capacity is available, 

regardless of current reservoir levels. By not explicitly 

modeling the reservoir levels at all of the hydro units, 

some of the water usage and non-power constraints and 

requirements found in actual unit operation are 

neglected. Some of these issues include: recreational 

water levels, irrigation, flood control, and dissolved gas 

levels. While they may greatly affect hydro generator 

production levels, the above named issues are also very 

unit and situation specific, making a full accounting of 

all possible constraints in all contingencies beyond the 

scope of a WECC-wide study such as WWSIS.

III. RESULTS

 Hydroelectric units can behave quite differently than 

thermal units in normal power system operations, and so 

case studies were performed to examine how the 

hydroelectric units might operate in a high variable 

generation scenario. Hydroelectric units have the 

advantage of being quick-start; however, they also have 

constraints on their generation based on maintaining 

reservoir levels within appropriate bounds. Since some 

hydro units have historically been used as load following 

units, with changes in production based on changes in 

forecast demand, case studies were performed to examine 

the difference in operations when the units were 

scheduled both before and after renewables. Additional 

analysis was conducted on the impact of using hydro 

generation as flat capacity (in order to fulfill reservoir 

water use constraints) instead of flexible generation on 

total system costs. Since the high levels of VG modeled 

require greater system flexibility, hydro power becomes a 

very valuable resource, as evidenced by the higher costs 

associated with flat hydro production when compared 

with flexible production.

A. Aggregate Hydroelectric Generation

Since some of the modeling assumptions in the 

WWSIS differ from current system operations; even in 

the no wind case, the operation of individual 

hydroelectric units should not be expected to perfectly 

mimic current operational practices. However, this does 

not mean that changes in operational patterns over the 

entire class of hydro units cannot be discerned. When

examining the output patterns of all hydro units in the 

different penetration rate scenarios, changes in hydro 

operation start to become apparent. For example, as 

seen in Figure 2, the hourly output levels do change 

slightly as the wind penetration level increases. 

However, the total monthly energy for hydro units 

remains constant and so the daily output may shift 

slightly from the day to the night, or vice versa, 

depending on the corresponding wind output. This 

difference can be quite significant. In Figure 2, on April 

14th, the difference between the no wind hydro output 

and 30% case is as large as 15 GW of power at one 

point. During times of lower wind power output, such as 

the month of July shown in Figure 3, the daily aggregate 

hydropower output patterns may still differ. However, 

the differences between the no wind case and high wind 

penetration scenarios are less significant than during 

times of high wind power output.

Figure 2 − Total hydro generation in the different In-Area wind 

penetration scenarios for the week of April 10th.
4

Figure 3 − Total hydro generation in the different In-Area wind 

penetration scenarios for the week of July 10th.

While the higher wind penetration rates can cause the 

hydroelectric units to operate quite differently at specific 

time points, overall changes in operational patterns are 

more important. One way to see the large scale 

differences in operation is by examining a generation 

duration curve for all hydro units over the course of a 

year. Figure 4 shows these curves for the no wind, 10%, 

20%, and 30% in-footprint scenarios. As may be 

observed, the curves are very similar for all four cases, 

showing that while the combined hydro production may 

be quite different at certain moments in time, the general 

pattern of usage is not significantly changed.

Figure 4 − Annual generation duration curve for all hydro units in 

WECC in the different In-Area wind penetration scenarios.

Another way of examining the patterns of change 

from high wind penetration is by viewing the hourly 

changes in production over the course of the year. 

Figure 5 shows the hourly change in production from all 

generators over the course of the year in a generation 

change duration curve. Once again, we can see that the 

duration curves are fairly similar for the three cases. In 

this case, we do observe a small difference in the 30% 

wind case at the relatively larger negative generation 

changes, with the high wind case actually producing 

slightly smaller negative changes in generation than the 

other cases.

Figure 5 − Annual hydro hourly delta duration curve for all WECC

hydro generation in the different In-Area wind penetration 

scenarios.

One place where the high wind power penetration 

rates make a significant impact is on the spot prices that 

occur during hydropower operation. As may be seen in 

Figure 6, there are noticeably lower spot prices across 

the entire year in the high wind penetration rates than in 

the no wind case. At the end of the spectrum with the 

lowest prices, the 30% wind cases have spot prices that 

are approximately $50/MWh lower than in the no wind 

case. These changes are to be expected due to the 

essentially zero marginal operating costs of wind plants, 

however, the overall loss in revenue for hydro generators 

implied by the lower spot prices is very important. 

Figure 6 − Spot price duration curve of hydro unit operation for the 

different In-Area wind penetration scenarios.

Finally, we examined an operational decision that can 

have a large effect on total system operating costs; 

whether to schedule hydro units based on total system 

load or net system load. We defined net load in this case 

as the load remaining after subtracting expected wind 

and solar generation from the load. Scheduling hydro 

units based only on load limits the utilization of their 

flexibility for balancing wind variability. The additional 

operating costs to the system for the 10%, 20%, and 30% 

wind penetration scenarios may be seen in Figure 7. The 

cost of this lost flexibility is relatively modest in the two 
5

lower wind penetration cases, but increases significantly 

in the 30% wind case.

Figure 7 − Operating cost increases for dispatching hydro based 

on only load versus net load for the different In-Area wind 

penetration scenarios.

B. Individual Units

As previously described, the assumptions made in the 

WWSIS dictate that the usage patterns of individual 

hydroelectric plants seen in the study will differ from 

those seen in current usage. Nevertheless, examining the 

usage patterns of the individual units can offer 

interesting insights, such as how hydropower plants 

might operate with fewer water usage constraints or in a 

system with larger balancing areas. Eight individual 

hydro generators operated by the U.S. Bureau of 

Reclamation and located in the WestConnect footprint 

were chosen for further study. The particular units

chosen are shown in Table I.

TABLE I 

HYDRO FACILITIES IN WESTCONNECT SELECTED FOR FURTHER STUDY

Plant Name Nameplate Capacity

Hoover Dam 2,074 MW

Glen Canyon Dam 1,296 MW

Davis Dam 240 MW 

Morrow Point Dam 173.2 MW

Blue Mesa Dam 86.4 MW

Mt. Elbert Pumped Storage Facility 200 MW

Parker Dam 120 MW

Crystal Dam 32 MW

Once again, we will use an output duration curve, this 

time to assess how the output of the selected hydro 

plants in the simulation compares to actual system 

operations. The aggregated output from the seven 

selected sites, not including the pumped storage facility, 

is compared for different wind penetration and siting 

scenarios against actual plant output from 2006 in Figure 

8. It is important to keep in mind that 10-year monthly 

average hydro plant output was used in the simulation, 

instead of actual 2006 output. Therefore, the total 

energy production in the simulation case is roughly 20% 

higher than in the actual 2006 output, as 2006 was a low 

output year for hydro. Even recognizing this fact, a clear 

difference in usage patterns is still noticeable. The 

simulated scenarios have a much wider range of usage 

than the actual output, with a higher instantaneous 

generation level and much more time at minimum 

generation levels as well. This implies that the 

simulation is cycling the hydro resources from high to 

low output more often than is seen in actual usage 

patterns. This is believed to be largely a result of the 

smaller number of balancing areas, freeing the hydro 

units from serving primarily as local balancing units. 

Figure 8 − Duration curve of aggregated output from the selected 

sites versus actual 2006 output for different wind penetration

scenarios. 

 To examine the impact of the hydro generator 

operating assumptions on system operations, another 

simulation run was performed where the nameplate 

capacity and monthly energy levels of the selected hydro 

units were de-rated to 2006 levels, based on the 

historical reservoir levels. As may be seen in Figure 9, 

the de-rating produces a duration curve for the sites that 

more closely resembles actual operations. However, the 

generator’s output still spends significantly more time in 

the higher and lower operating regions than is observed 

in historical operations.

Figure 9 − Duration curve of aggregated output from the selected 

sites versus actual 2006 output for different wind penetration 

scenarios after adjusted the maximum capacity and monthly 

energy levels based on historical data.

The differences in unit operation patterns can best be 

observed by examining an individual unit at a shorter 
6

timescale. Figure 10 shows the hourly dispatch for the 

Hoover dam over a one week period in July for actual 

unit operations, a no wind case, and a 20% penetration 

scenario. Both of the simulated cases display much 

more consistent unit behavior than the historical data. 

The simulated cases switch between high output and 

minimum output in a diurnal step-function pattern. The 

historical data, on the other hand, shows much greater 

variation in output, suggesting that it is being used for 

load following, along with its primary purpose of water 

flow control. This same phenomenon can be observed

only during some of the days shown in Figure 11, which 

is based on an April week with higher wind output. The 

fact that the simulation does use the same unit for load 

following, albeit less often than historical operations 

would suggest, is likely the result of the lesser number of 

balancing hours used in the simulation than in actual 

operations. This allows the hydro generator to serve as a 

baseload unit more frequently.

Figure 10 − Hourly dispatch from Hoover Dam during a one-week 

period in July 2006 for actual operations, a no wind case, and a 

20% penetration scenario.

Figure 11 − Hourly dispatch from Hoover Dam during a one-week 

period in April 2006 for actual operations, a no wind case and a 

20% wind penetration scenario.

C. Flat Block Hydro

The flexibility of hydroelectric generators to start and 

ramp quickly is expected to be an important attribute with 

increasing VG penetration. In order to help assess the 

value of hydropower being able to balance system 

variability, a comparison was performed between two 

modes of hydro operation; allowing hydro units to be 

dispatched and grouping all hydropower together as a flat 

block. In the flat block case, the hydro units were 

restricted to producing at a fixed rate during all times of 

the day, with the production level varying from month to 

month, based on the seasonal monthly production 

averages. Figure 12 shows an example of the difference 

in the two types of hydro operation at the Hoover Dam.
7

Figure 12 − Average production at Hoover Dam by hour of day for 

each month in the hydro dispatching and flat block cases [11].

The total system operating costs for a variety of wind 

penetration scenarios, both with and without flat hydro 

blocks, are displayed in Figure 13. Immediately 

noticeable are the decreasing total system operating costs 

with higher penetrations of wind energy due to the zero 

marginal cost of wind power. Also immediately apparent 

are the higher costs in every scenario when a flat hydro 

block is used instead of allowing hydro to be dispatched.

Figure 13 − Total system operating cost changes due to flat block 

hydro operation for the different In-Area wind scenarios.

Figure 14 provides a closer look at the differences in 

cost between the dispatchable and flat hydro cases. An 

interesting result is that the absolute increase in 

operating cost between the two forms of hydro operation 

is lower for each of the wind penetration cases than for 

the no wind case. However, one must also remember 

that the total operating costs are lower in the high wind 

penetration scenarios. Therefore, the relative decrease in 

total operating costs are fairly similar for all the cases, 

with the highest wind penetration rates having slightly

higher cost increases when using the flat block 

operation.

 

Figure 14 − Incremental operating cost increase due to flat block 

hydro production in the various In-Area penetration rate scenarios.

Another way to assess the impact of the flat block 

hydro operating policy is through the examination of the 

spot price duration curve. Figure 11 shows this curve 

for the no wind and 30% penetration scenario for both 

hydro operation modes. The flat block operation of 

hydro units has an amplifying effect in the no wind case. 

During times of high spot prices, the flat block creates 

even higher prices by not being available as a cheap 

dispatch solution. In the lower price cases, which most 

often occur during times of low system load, the flat 

hydro block further reduces system prices. In the 30% 

wind scenario, the dispatchable and flat block cases are 

very similar for most of the year. It is only during the 

lowest cost hours that the flat block case further reduces 

the spot price. 

Figure 15 − Spot price impact of flat block hydro in the no wind 

and 30% wind penetration In-Area scenarios.

2 4 6 8 10 12 14 16 18 20 22 24

0

500

1000

1500

Diurnal Plots -- Hoover L20R

Hour

Average Daily Generation (MW)

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

2 4 6 8 10 12 14 16 18 20 22 24

0

500

1000

1500

Diurnal Plots -- Hoover L20R-Hf

Hour

Average Daily Generation (MW)
8

IV. CONCLUSION

In this report, we have examined the impact that high 

wind power penetration rates will have on hydroelectric 

unit operations in the western United States. Since 

hydroelectric generator’s flexibility is often seen as the 

perfect complement to variable and uncertain wind and 

solar power, it is important to schedule the hydro 

generation based on expected net load instead of load 

alone, to better utilize this flexibility. Another important 

result is the establishment of the significant total system 

cost increases that arise from not utilizing this flexibility, 

as was determined by examining flat-block hydro 

operation. It is important to note that the operation of 

hydro units is often strongly influenced by non-power 

considerations. To more accurately establish the effects 

of high wind penetrations on hydro system operations, 

these non-power constraints must be modeled on a unitby-unit basis, a difficult task due to modeling and data 

availability limitations. In summary, the flexibility of 

hydro units can be an important factor in reducing total 

system costs, so long as that flexibility is made available 

to the system.

V. REFERENCES

[1] GE, "Western Wind and Solar Integration Study," 

NREL/SR-550-47434, 2010.

[2] C. Potter, D. Lew, J. McCaa, S. Cheng, S. 

Eichelberger, and E. Grimit, "Creating the Dataset for 

the Western Wind and Solar Integration Study," Wind 

Engineering, vol. 32, pp. 325 - 338, 2008.

[3] M. Milligan and B. Kirby, "Market Characteristics 

for Efficient Integration of Variable Generation in the 

Western Interconnection," National Renewable 

Energy Laboratory, Golden, CO2010.

[4] C. Belanger and L. Gagnon, "Adding wind energy to 

hydropower," Energy Policy, vol. 30, pp. 1279 - 

1284, 2002.

[5] J. K. Kaldellis, K. Kavadias, and E. Christinakis, 

"Evaluation of the wind-hydro energy solution for 

remote islands," Energy Conversion and 

Management, vol. 42, pp. 1105 - 1120, 2001.

[6] C. Bueno and J. A. Carta, "Wind powered pumped 

hydro storage systems, a means of increasing the 

penetration of renewable energy in the Canary 

Islands," Renewable and Sustainable Energy 

Reviews, vol. 10, pp. 312 - 340, 2006.

[7] M. Milligan, K. Porter, E. DeMeo, P. Denholm, H. 

Holttinen, B. Kirby, N. Miller, A. Mills, M. 

O'Malley, M. Schuerger, and L. Soder. (2009) Wind 

Power Myths Debunked: Common Questions and 

Misconceptions. IEEE Power & Energy. 89 - 99. 

[8] L. Benitez, P. Benitez, and G. C. van Kooten, "The 

economics of wind power with energy storage," 

Energy Economics, vol. 30, pp. 1973 - 1989, 2008.

[9] E. Castronuovo and J. Lopes, "On the Optimization 

of the Daily Operation of a Wind-Hydro Power 

Plant," IEEE Transactions on Power Systems, vol. 

19, pp. 1599 - 1606, August 2004.

[10] M. Korpaas, A. Holen, and R. Hildrum, "Operation 

and sizing of energy storage for wind power plants in 

a market system," International Journal of Electrical 

Power & Energy Systems, vol. 25, pp. 599 - 606, 

2003.

[11] T. Acker and C. Pete, "Western Wind and Solar 

Integration Study: Hydropower Analysis," NREL - 

Northern Arizona University 2011.