Research on short-term power load forecasting based on Elman neural network with Genetic Algorithm

Abstract

The electric power industry is closely related to the development of national economy. With the development of economy, the social electricity situation is increasingly complicated, which brings great test to the prediction of electric load system. Accurate short-term power load forecasting plays an important role in production scheduling and safe and stable operation of power system. In this paper, Elman neural network based on genetic algorithm is established and a short-term power load forecasting model is established. The actual history data of municipal power grid are simulated, the experimental results show that compared with the BP neural network and Elman neural network commonly, Elman neural network based on genetic algorithm to solve the problem of random initial weights of the Elman neural network, can effectively enhance the power load forecasting accuracy and meet the needs of the actual production and work.