Research on the Substitute Potential of Beijing-Tianjin-Hebei Electric Energy under Multiple Scenarios Based on PSO-SVM Algorithm

Abstract

To control the haze of Beijing-Tianjin-Hebei, the government has promoted the “electric energy substitution” (EES)strategy of replacing scattered coal and direct fuel with electric energy. In order to explore the potential of EES in Beijing-Tianjin-Hebei region, this paper takes GDP, population, and technological progress as influencing factors, considers multiple scenarios based on the “decoupling” theory, and establishes a regional energy substitution potential prediction model based on particle swarm optimization support vector machine(PSO-SVM). The market potential of electric energy substitution is predicted and analyzed through scenario analysis. Based on the prediction results, suggestions for promoting electric energy replacement strategy are proposed.