Utility Sector Wind Power Forecasting: Status and Measurement Needs

1. Utility Sector Wind Power Forecasting: Status and Measurement Needs 23rd Conference on Weather Analysis and Forecasting/19th Conference on Numerical Weather Prediction American Meteorological Society Marc Schwartz Erik Ela June 2, 2009 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

2. Organization of Presentation • Current Status of Wind Generation Forecasting • Specialized Wind Forecasting Problem • Current Wind Forecasting Projects

3. Wind Energy Generation 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 National Renewable Energy Laboratory Innovation for Our Energy Future

4. 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

6. 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

7. 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

8. 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

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

10. Bonneville Power Administration Service Area

11. BPAWind 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

12. 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

13. 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