The forecast of the electric power load is related to the development of economy. It is also related to the national security and the daily operation of the society. The result of the power load forecasting is not only directly related to the economic benefits of the power enterprise, but also is very important to the users. From improving the accuracy of the power load forecasting, this paper proposes an improved Elman neural network algorithm to predict the power load. Then, we analyze and compare the experimental results by the numerical experiments. We find that the experimental results are better than the traditional prediction algorithm. The experimental results show that the algorithm is reliable and effective.
