NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy operated by the Alliance for Sustainable Energy, LLC

23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather PredictionAmerican Meteorological Society

Marc SchwartzErik Ela

June 2, 2009

Utility Sector Wind Power Forecasting: Status and Measurement Needs

2

Organization of Presentation

Current Status of Wind Generation Forecasting

Specialized Wind Forecasting Problem

Current Wind Forecasting Projects

National Renewable Energy Laboratory Innovation for Our Energy Future

Status of Wind Generation in U.S. and Forecasting Industry

• 25.2 gigawatts (GW) of installed wind capacity in the U.S. at the end of 2008

• Total installed capacity expected to reach 30 GW by end of 2009

• Wind generation forecasting is a commercial industry

Wind Energy Generation

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Need for Accurate Wind Generation Forecasts

System operators are required to balance electric generation and load within a tight range– If wind power is declining other generation must increase to

keep electric system balanced

A under-forecast of wind generation leads to:– Starting generation units that are not needed– Higher costs

An over-prediction of wind generation leads to:– Possible use of expensive fast-start combustion turbines– Higher costs– Potential system reliability issues

5

Selected System Operators in Major Electricity Markets

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Time (hour of day)0 4 8 12 16 20 24

Sy

ste

m L

oa

d (

MW

)

seconds to minutes

Regulation

tens of minutes to hours

LoadFollowing

day

Scheduling

Days

UnitCommitment

Time frames that affect operations of electric power systems

• Typical time frames for wind generation forecasts: - hourly for day-ahead - hourly or sub-hourly for same day

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Wind Generation Forecasting Techniques

Forecasts for periods greater than several hours in advance area 2-step process– Wind speed forecasts are derived from numerical models

• Ensemble techniques becoming popular. These can help define forecast uncertainty

– Speed forecasts are converted to power generation forecasts (in megawatts of production)

Forecasts for 0-3 hours from forecast time use statistical techniques– Kalman filters, regression equations, neural networks– Historical power output data from wind plants and

meteorological data from on-site are critical inputs

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Wind Generation Ramp Forecasting

Rapid increases or decreases in wind generation output in short period of time– +/- 20% or greater change in output in 30 -120 minute period

Wind ramps tests system operators in maintaining the quality of electricity system

Developing a ramp forecasting tool presents challenges– Factors that cause a wind ramp are varied

• Synoptic conditions• Thermal circulations• Mesoscale convective events

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Example of Downward Ramp of Wind Generation in ERCOT area in February, 2008

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Bonneville Power Administration Service Area

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BPA Wind Ramp Forecasting Project

BPA needs wind ramp forecasting tool to minimize hydro-power needed for backup– BPA expects to have 6000 MW of wind on-line by 2013– Hydro-power needs 4-hour response time for backup– Using hydro-power as backup reduces BPA’s ability to sell

surplus power capacity to surrounding regions

Two commercial vendors will develop and test wind ramp forecasting tools– Verification of wind ramp forecasts is a challenge

• No standard verification metrics exist• Designing metrics that reflect usefulness of forecasts to system

operators

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Current Wind Forecasting Project

Xcel project with NREL and NCAR– NREL will research converting wind speed forecasts to wind

generation forecasts• Output from individual turbines will be combined with data from

meteorological towers• Artificial neural networks will be used to identify factors that influence a

wind plant power curve

– NCAR working on large field campaign to evaluate how a high spatial resolution offsite atmospheric data network can:

• Improve forecast accuracy • Develop a robust wind characterization program

2-year project started in late 2008– Initial results available in late 2009/early 2010

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Conclusions

Wind generation forecasting rapidly being adopted by utilities and ISOs– Accurate forecasts needed to integrate wind generation into

electricity grid

Specialized wind forecasting problems have emerged – Accurate wind power ramp forecasting

Projects such as Xcel/NCAR/NREL will provide public data on:

– Conversion of wind speed forecasts to wind generation forecasts– The results of adding offsite measurements (wind, temperature, and

pressure) on forecast accuracy and wind characterization