Power Load Forecasting Based on BP Neural Network

Abstract

Load prediction of power system plays an important role in real-time control and ensuring economic, safe and reliable operation of power system. At the same time, the variation of power load system parameters is affected by many factors, which will lead to the nonlinear development of load curve. In this paper, a prediction method based on BP neural network is proposed. The biggest advantage of this method is that it has adaptive function to a large number of nonlinear characteristics and non-accuracy laws. This paper mainly focuses on the application of BP neural network in short-term load prediction of power system to do further research, and through MATLAB BP neural network design, simulation results show that the application of BP neural network in short-term load prediction is feasible, can better reflect the nonlinear characteristics of load prediction. However, because this paper does not consider the effects of climate, temperature, holidays and other factors, there is still a certain gap between the simulation results and the ideal results, but it is certain that BP neural network is still better than the traditional prediction method, is a very promising new research and development field.