In order to improve the accuracy and stability of wind power prediction to better cope with the variabil-ity and nonlinear characteristics of wind speed,this paper proposes a wind speed prediction model(SSA-RBFN)based on the SSA optimized radial basis function(RBF)neural network.The parameters of RBFN are optimized by SSA to predict and improve the accuracy and stability of the model.By selecting actual data from wind farms for the study and comparing with SSA-BP model,RBF model,and BP model,the simulation results show that the SSA-RBF prediction model is reflected in the MAE,MBE,and RMSE indexes,and the prediction error is signifi-cantly lower than that of the traditional RBF and BP models,which indicates that the proposed model is feasible and effective.
关键词
风速预测/麻雀搜索算法/径向基函数神经网络/预测模型优化
Key words
wind speed prediction/sparrow search algorithm/radial basis function neural network/prediction model optimization
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万方数据