Research on electric load forecasting based on RBF

Accurate power load forecasting is of great significance for grid planning and economic operation of power systems. In order to improve the accuracy of power load forecasting, this paper proposes a short-term power load forecasting method based on particle swarm algorithm (PSO) optimized radial basis (RBF) neural network. The method takes RBF neural network as the basic algorithm for short-term load forecasting. Considering the problems of the algorithm’s parameter setting and the tendency to be trapped in the local optimum, the PSO algorithm is used to optimize the parameters of the algorithm, so as to obtain a better forecasting model. The experimental results show that the proposed algorithm can improve the prediction accuracy to a certain extent and has certain practical application value.