Research on Wind Power Prediction Method Based on GA-BP Neural Network
To solve the problem that wind power prediction is susceptible to the influence of various factors that produce abnormal data leading to low prediction accuracy,a wind power prediction method based on genetic algorithm-back propagation(GA-BP)neural network is proposed.Firstly,the abnormal datas are identified by the quartile algorithm in the mathematical model,and the abnormal datas are eliminated by adding a band-pass filter.Then,a novel GA-BP neural network algorithm is designed on the method of wind power prediction,and accurate wind power prediction results are obtained by self-testing and cyclic detection.The experimental results show that the method not only has a strong ability to recognize abnormal data,but also can maintain more than 90%accuracy when performing wind power prediction with good data processing stability.This study greatly improves the efficiency of wind power prediction and provides technical reference for the further development of wind power prediction technology.
Wind power predictionNeural networkAbnormal data identificationGenetic algorithm(GA)Back propagation(BP)Cycle detectionQuartile algorithm
NETL
NSTL
万方数据
