Aiming at the problems of low accuracy and poor accuracy of short-term load forecasting, a short-term load forecasting method based on cat swarm algorithm CSO and BP neural network is proposed in this paper.The input factors of the model are load data and meteorological information, cat swarm optimization algorithm is used to optimize the weight and threshold of BP neural network, so that the BP neural network forecasting model can be optimized, a short-term load forecasting model of BP neural network based on Optimization of cat swarm algorithm is established.The accuracy and validity of the prediction model are verified by simulation, the results show that the improved model can effectively reduce the prediction error of BP neural network model and improve its prediction accuracy.This study provides a reference for the development of short-term load forecasting of power system in China.