Research on Load Forecasting of Power Systems Based on GA-BP Neural Network

Aiming at the problem of low accuracy of short-term load forecasting in power system, this study combines genetic algorithm GA and BP neural network to establish a short-term forecasting model for power system load forecasting. Firstly, the weights and thresholds of BP neural network are optimized using genetic algorithm GA to get the optimal solution of BP neural network prediction model. Then the validity of the prediction model is verified by examples. The results show that the improved model can effectively reduce the measurement error of the BP neural network model and improve the prediction accuracy, which provides a reference and reference for the development of short-term load forecasting in China's power system.