Research on supply and demand situation of fossil energy in Hunan province based on improved PSO-BPNN

In view of the new changes in the energy supply and demand pattern, this paper established a PSO-BP neural network model based on the sliding window method to predict the supply and demand situation of the three fossil energy sources of coal, crude oil and natural gas.According to the forecast results, PSO-BPNN model based on sliding window method can well predict the changes of energy supply and demand, the improved PSO-BPNN model can well fit the energy supply and demand changes in Hunan province or other regions.And it’s obviously better than GA-BPNN, ARIMA and GM(1, 1) model.By analyzing the results, it’s found that although the demand growth of the three fossil energy sources is gradually weakening, the gap is still large.Except for crude oil and natural gas without production capacity, the provincial guarantee rate of coal is about 80%.With the use of natural gas, it is estimated that the supply and demand situation of fossil energy in Hunan province will enter a stage of profound adjustment in the short term.Finally, for the development trend of the supply and demand of three fossil energy sources, this paper also discusses the prediction results and puts forward relevant suggestions to provide data and theoretical support for the promotion of energy reform in Hunan province.