Research on Electricity Demand Forecasting Method Based on Classification-Correlation-Correction
Electricity demand is so volatile that it is difficult to predict.A electricity demand forecasting method based on classification-correlation-correction is proposed for macro electricity demand prediction of regional power grids.Gray correlation analysis method is used to screen out the key industries'electricity consumption,as well as the factors that affect each industry's electricity consumption to a greater extent.On the basis of the traditional regression forecasting method,it combines the gray forecasting method to forecast the influencing factors of electricity demand and establishes a regression forecasting model of electricity demand.The ratio of industrial electricity to the whole society's electricity is used to correct the model's forecast value,so as to improve the forecasting accuracy.Compared with the overall forecasting method,it verities that the method carries out the identification of key influencing factors and power demand forecast by industry and makes macro correction.Based on the power data of Henan province from 2011 to 2022,it verifies that the method can accurately predict the future development trend of power demand,which can provide a reference basis for the long-term warning of the regional power grid.
Electricity demand forecastingGrey correlation analysisGrey forecastingRegression analysisRatio of electricityParameter correction
NETL
NSTL
万方数据
维普
