Application of Back Propagation Neural Network for Wind Power Generation Forecasting

Abstract The power generation of wind energy conversion system (WECS) is varied with wind speed. Although wind power generation is not dispatch able, an accurate forecasting method of wind power generation for WECS can help the power system operator to reduce operating costs of power system. The artificial neural network is one of the best tools applied to forecast. This paper uses the back propagation neural network to forecast the wind power generation of WECS. To demonstrate the effectiveness of the proposed forecasting method, the method is tested on the practical information of wind power generation of a WECS. The good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.