Research on electricity spot market price prediction model based on PSO optimization LS-SVM

In this paper, a prediction model based on PSO optimized LS-SVM is proposed. In view of the complex fluctuations of electricity price in the electricity spot market and the characteristics of being affected by many factors, this study uses the strong nonlinear mapping ability and good generalization performance of LS-SVM model, combined with the global optimization search strategy of PSO algorithm, the parameters of LS-SVM model are intelligently optimized. The experimental results show that the PSO optimized LS-SVM model proposed in this paper significantly reduces the prediction error in the electricity spot market price prediction, and can better capture the dynamic characteristics of electricity price changes. The research results provide an effective electricity price prediction tool for power market participants.