Wind Power Prediction Based on BPNN and LSA

Abstract

Wind power is a very universal power generation technology in recent years. China's wind power technology has come to large-scale development stage. Because of its intermittence, instability, hard-predictability, especially when it parallels in the whole grid, it can bring great influence to the stability and safety of the whole power grid. In order to solve the problem of wind power, it is necessary to predict wind power. There are two commonly used methods. Through the forecasted wind speed on BP neural network (BPNN) prediction methods, combining with the wind speed and power, the paper conducted wind-power prediction. Another is directly power prediction based on the speed and power data. Applying least-square regression analysis, the results of relationships of speed, temperature and power can be easily achieved. What's more, this paper applied time-sequence method in preliminary wind speed prediction. With SPSS software, this paper mapped the changing characteristics of the sequence.