Short-term power load forecasting model based on IGWO-Attention-GRU
In order to improve the accuracy of short-term power load forecasting,a short-term power load forecasting model based on Improved Grey Wolf Optimization(IGWO)algorithm to optimize Attention-GRU network is proposed on the basis of the characteristics of strong fluctuation and high complexity of power load series,as well as the influence of meteorological factors and date types.Firstly,the Attention-GRU network is constructed.Secondly,the IGWO algorithm is improved,and IGWO is used to find the hyper-parameters of Attention-GRU network.Finally,the IGWO-Attention-GRU model is used to carry out experi-ments on power load data sets,and compared with various forecasting models.The experiment results show that the MAPE,RMSE and MAE values of IGWO-Attention-GRU model are the lowest among various fore-casting models,which verifies the superiority of IGWO-Attention-GRU model.
short-term power load forecastingGRU networkAttention mechanismImproved Grey Wolf Optimizationhyper-parameter optimization
万方数据
维普
