A Meteorological–Statistic Model for Short-Term Wind Power Forecasting

[摘要] The problem of wind power forecasting is addressed in this work, considering a combination of a numerical weather prediction model (NWP) and statistical models. Brazilian developments on the Regional Atmospheric Modeling System is employed in two different areas in Brazil to simulate forecasts of 72 h ahead of the wind speed, at each 10 min. In one of the areas studied, the wind speed is converted into wind power. Different conversion methods are employed and discussed. Kalman filtering techniques are employed to reduce systematic error of the forecasts, both wind and generation. Each 72-h period of the NWP simulations had a computational time of approximately 60–70 min using indicating that the proposed method can be applied in real time for power system operation. The results obtained are very encouraging for further investigation to achieve more accurate wind power researches.

[学科分类] 自动化工程

[关键词] Wind power forecast ;Numerical weather prediction models ;Kalman filtering ;Power curve