Brian Parsons

National Wind Technology Center

National Renewable Energy Laboratory

Golden, Colorado USA

European Wind Energy Conference 

Athens, Greece

February 27 – March 2, 2006

Grid Impacts of Wind Power Variabi

Assessments from a Variety of Utilities in t

NREL/PR-500-39524
Disclaimer and Government License

This work has been authored by Midwest Research Institute (MRI) under Contract No. DE-AC36-Department of Energy (the “DOE”). The United States Government (the “Government”) retains athe work for publication, acknowledges that the Government retains a non-exclusive, paid-up, irrepublish or reproduce the published form of this work, or allow others to do so, for Government puNeither MRI, the DOE, the Government, nor any other agency thereof, nor any of their employeesor implied, or assumes any liability or responsibility for the accuracy, completeness, or usefulness product, or process disclosed, or represents that its use would not infringe any privately owned rig

specific commercial product, process, or service by trade name, trademark, manufacturer, or otheimply its endorsement, recommendation, or favoring by the Government or any agency thereof. Tauthors and/or presenters expressed herein do not necessarily state or reflect those of MRI, the Dagency thereof. 
Acknowledgement

Thanks to co-authors:

Michael Milligan, NRELJ. Charles Smith, Utility Wind Integration Group

Edgar DeMeo, Renewable Energy Consulting 

Brett Oakleaf, Xcel Energy

Kenneth Wolf, MinnCommission

Robert Zavadil, Enernex CorporationDora Yen Nakafuji, California Energy Commission

Critical review/input from Nicholas Miller and RichaKevin Porter, Exeter Associates, and Henry Shiu, 

Matt Schuerger, Energy Systems Consulting Services, LLC

Mark Ahlstrom, WindLogics
Presentation Outline

• Issues and time frames of importa

• Methods and approaches

• Four recent studies

– Minnesota DOC/Xcel North– NYSERDA/GE New York State

– Xcel Colorado

– California Multiyear RPS Integration 

• Comparison with previous studies

• Conclusions and remaining issue

• Ongoing/future work 
Wind Variability

Can Increase Power System Operatin

• Committing unneeded generation • Allocating extra load-following capability• Allocating additional regulating capacity • Increased cycling operation• These are reflected in ancillary servic

0

200400600800

10001200

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 

Time (hh:mm)

Wind Power

Load

Load 

(MW)
Time (hour of day)

048 12 16 20 24

System Load (MW)

seconds to minutes

Regulation

tens of minutes to hours

Load

Following

day

Scheduling

Days

Unit

Commitment

• Regulation 

minutes -- 

customer d

• Load-follow

to a few ho

predictable 

• Scheduling 

generating days -- win

Wind Variability

Power System Operation Imp

Typical U
Methods 

Emerging Best Practice

• Capture system characteristics and resp

operational simulations and modeling

• Capture wind deployment scenario geo

diversity through synchronized weather 

• Couple with actual historic utility load an

forecasts

• Use actual large wind farm power statis

short-term regulation and ramping

• Examine wind variation in combination w

variations

• Utilize wind forecasting best practice an

wind forecast errors with load forecast e

• Examine actual costs independent of ta

structure
Minnesota Dept. of Comm

Enernex Study Framew

• 2010 scenario of 1500 MW of 

wind in 10 GW peak load system (< 700 MW wind currently)

• WindLogics:10-minute power 

profiles from atmospheric modeling to capture geographic diversity

• Wind forecasting 

incorporated

• Extensive historic utility load 

and generator data available

• Monopoly market structure, 

no operating practice modification or change in conventional generation expansion plan
Minnesota Dept. of Com

Enernex Study Resu

• Incremental regulation due to 

wind 3

σ = 8 MW

• Incremental intra-hour load 

following burden increased 1-2 MW/min. (negligible cost)

• Hourly to daily wind variation and 

forecasting error impacts are largest costs

• Monthly total integration cost: $2- $11/MWh, with an average of $4.50/MWh

• Capacity Credit (ELCC) of 26%

Completed September 2004 www.commerce.state.mn.us(Industry Info and Services / Energy Utilities / Energy Policy / W
New York ISO and NYSER

GE Energy Study

• 2008 scenario of 3300 MW of 

wind in 33-GW peak load system (< 200 MW wind currently)

• AWS Truewind: wind power 

profiles from atmospheric modeling to capture statewide diversity

• Competitive market structure:

- for ancillary services

- allows determination of generator and consumer pay

• Transmission examined: no delivery issues• Post-fault grid stability improved with modern 

684

358

570
0

5000

100001500020000250003000035000

1 25 49 73 

Hour 

NYISO Load (MW)

W

New York ISO and NYSE

GE Energy Study Impa

• Incremental regulation of 36 

MW due to wind

• No additional spinning 

reserve needed 

• Incremental intra-hour load 

following burden increased 1-2 MW/ 5 min. 

• Hourly ramp increased from 

858 MW to 910 MW

• All increased needs can be met by existing NY 

market processes

• Capacity credit (UCAP) of 10% average onshor

offshore

• Significant system cost savings of $335- $455 

assumed 2008 natural gas prices of $6.50-$6.80 
New York ISO and NYSE

GE Energy Study 

http://www.nyserda.org/publications/wind_integ

Forecasting and Price Imp

• Day-ahead unit-commitment 

forecast error 

σ increased from 

700-800 MW to 859-950 MW

• Total system variable cost savings increases from $335 million to 

$430 million when state of the art forecasting is considered in unit commitment ($10.70/MWh of wind)

• Perfect forecasting increases savings an additional $25 million 0

200400600800

1000

15000 20000 

Peak Load fo

S ig m a (M W )

Load 

8

W

Standard Deviations 
Xcel Colorado/Enernex S

• 10%, 15%, and 20% 

penetration (wind nameplate to peak load) examined for ~7 GW peak load

• Gas storage & nominations

– Gas imbalance

– Extra gas burn for reserves

• Gas price sensitivity

• Transmission constraints

• O&M increase for increased 

start/stops 

• Real-time market access

Ponn
Xcel Colorado/Enernex 

Penetration 

Level 10% 15% 

Hourly Analysis $2.26/MWh $3.32/MWh 

Regulation $0.20/MWh $0.20/MWh 

Gas Supply (1) $1.26/MWh $1.45/MWh 

Total $3.72/MWh $4.97/MWh 

(1) Costs includes the benefits of additional gas storage

(2) Rough results based on scaling wind generation without ge

Preliminary Results

– pending final report anticipated in April 2006

• Without cycling of 300 MW pumped hydro 

would be $1.30/MWh higher
Gas Storage Benefits/R

• Summer/winter arbitrage 

– Cost savings in filling in summer a

withdrawing in winter

• Reduction in need for financial hedg

– Because the price of the gas in th

is known, there is no need to finanthe market price of the gas 

Wind Penetration 10% 

$/ MWH Gas Impact No Storage Benefits $2.17 $$ / MWH Gas Impact With Storage Benefits $1.26 $

20% results based on scaling wind generation without geographic diversit
CA RPS Integration Cost P

• Examining impacts of existing installe

renewables (wind 4% on a capacity b

• Calculated regulation, load following i

renewables

• Capacity value (ELCC) for all renewa• Regulation cost for wind $0.36/MWh • Load following: minimal impact

• Wind capacity credit 23%-25% of ben

unit

http://cwec.ucdavis.edu/rpsintegration
• Data from PI (power information) system

– compression may artificially smooth high-re

data

– Missing data correction algorithm introduced 

in wind data

• Complex system influences wind capac

– Scheduled maintenance of conventional gen– Hydro dispatch– Interchange schedule

• Multi-year analysis will be released by C

now: regulation impacts similar to 1-yeacapacity value shows some fluctuation yload following impact still difficult to dete

CA RPS Lessons Lea

Data and Modeling Assumptions 
Comparison of Cost-Ba

U.S. Operational Impact S

Date Study Wind 

Capacity Penetration (%)

Regulation Cost 

($/MWh)

Load Following Cost ($/MWh)

Unit Commitment Co

($/MWh

May ‘03 Xcel-UWIG 3.5

0 0.41 1.44 

Sep ‘04 Xcel-MNDOC 15 0.23 na 4.37 

July ‘04 CA RPS 

Phase III

4 0.36 (1) na na 

June ‘03 We Energies

4 1.12 0.09 0.69 

June ‘03 We Energies 29 1.02 0.15 1.75 

2005 PacifiCorp 20

0 1.6 3.0 

April ‘06 Xcel-PSCo 10 0.20 na 2.26 

April ‘06 Xcel-PSCo 15 0.20 na 3.32 

April ‘06 Xcel-PSCo (2) 20 0.20 na 6.57 

(1) Represents corrected value (2) Preliminary results based on scaling wind generation
Factors that Influence Re

• Balancing area size 

– Conventional generation mix– Load aggregation benefits

• Wind resource geographic div• Market-based or self-provided 

services
Conclusions and Insi

• Additional operational costs are modera

penetrations at or above portfolio stand

• For large, diverse electric balancing are

regulation and load following resources markets are adequate, accompanying c

• Unit commitment and scheduling costs 

dominate

• State of the art forecasting can reduce c

– majority of the value can be obtained with cu

the-art forecasting

– additional incremental returns from increasin

forecasts 

• Realistic studies are data intensive and 

sophisticated modeling of wind resource system operations
Some Remaining Iss

• Higher wind penetration impacts

• Effect of mitigation strategies

– Balancing area consolidation and dy

scheduling

– Complementary generation acquisit

system design) and interruptible/pricload

– Power system operations practices 

control/curtailment

– Hydro dispatch, pumped hydro, othe

markets (plug-hybrid electric vehicle

• Integration of wind forecasting an

measurements into control room 
Future/Ongoing Wo

(Enernex, WindLogics, Ariva, UWI

• 2006 Minnesota Wind Integration Study

– Statewide, 20% by energy (5 GW wind)

– New MISO market structure– Examine transmission & mitigation strategie– Comparison of market operational and relia– Completion date 11/06

• Xcel (MN) Renewable Development Fu

Room Integration of Wind

– Define, design, build and demonstrate a com

power forecasting system for use by Xcel sy

– Optimize the way that wind forecast informa

into the control room environment

– R&D on defensive operating strategies: Valu

towers, high wind warning system, rapid updmodel
• California Energy Commission Intermitt

Project

– 5 GW of wind by 2010, up to >10 GW by 20

capacity)

– Will consider whether mitigation measures a

certain times (such as low load, high wind p

– Lead contractor: GE Energy with wind resou

by AWS Truewind

– Completed by end of 2006

• Smaller balancing authority projects

– Sacramento Municipal Utility District: high p

investigate value of pumped hydro

– Public Service of New Mexico: limited conve

resources, high ramping wind, export and m

issues

– Idaho Power and Grant County projects: inte

constrained existing hydro

More Future/Ongoing W
Increasing Attention in North A

• IEEE Power 

Society MagNovember/D

• Utility Wind 

Group (UWIImpacts and Studies User 

• www.uwig.o