A Short-term Load Forecasting Method Considering Multiple Influencing Factors

Abstract

In this paper, a short-term load forecasting technology considering multiple influencing factors is proposed to improve the reliability of short-term load forecasting from the two aspects of influencing factors and model selection. Firstly, the influence factors of power load are summarized and analyzed, and then the influencing factors are optimized and sorted by the XGBoost algorithm. Finally, the short-term load forecasting results are obtained by RNN and LSTM training model. Simulation results show that the proposed method has good accuracy.