Accurate Hour Ahead Wind Energy Forecasts: Off-site Observations and Numerical Weather Prediction
A special presentation on highly accurate predictions of wind power for producing renewable energy. Presented by Kristin Larson of 3Tier.
Thursday, May 26, 2011
12:00 PM - 1:00 PM
La Kretz Hall, Suite 300, Large conference room
Dr. Larson's background is in mesoscale modeling, statistical methods, and climate scale dynamics. In her position as Manager of Wind Energy Forecasting, Dr. Larson leads 3TIER's operational wind energy forecasting. She has over 8 years experience in realtime wind energy forecasting and has given numerous wind energy presentations.
With the global proliferation of wind power, accurate short-term forecasts of wind resources at wind energy sites are becoming paramount.
Regime-switching space-time (RST) models merge meteorological and statistical expertise to obtain accurate and calibrated, fully probabilistic forecasts of wind speed and wind power. The model formulation is parsimonious, yet takes account of all the salient features of wind speed: alternating atmospheric regimes, temporal and spatial correlation, diurnal and seasonal non-stationarity, conditional heteroscedasticity, and non-Gaussianity. The RST method identifies forecast regimes at the wind energy site and fits a conditional predictive model for each regime. Geographically dispersed meteorological observations in the vicinity of the wind farm are used as off-site predictors. For each month in the test period, the RST forecasts had lower RMSE than forecasts using state-of-the-art vector time series techniques.
In combination with the RST method, fine-scale numerical weather predictions can also be used to further increase forecast accuracy at short forecast horizons. Significant forecast improvements are feasible when using off-site observations and meso-scale numerical weather predictions are combined in statistical forecast algorithms.
Global methods for determining which off-site observations to use at a particular wind project are discussed. Numerical weather prediction simulations and an adjusted distance scaling based on the prevailing wind direction are both useful methods.
These techniques can be used to increase hour ahead forecast accuracy at wind energy sites all over the world. Timely and accurate short-term forecasts can increase the electric grid efficiency and minimize ancillary or other firming requirements, ultimately resulting in reduced costs.
Sponsor(s): Center for Climate Change Solutions