Multi-time Scale Load Forecasting Based on Wavelet Threshold Denoising and Prophet

Abstract

Using historical data to predict future energy demand of power system plays a key role in solving the challenge of supply and demand balance of power system brought by renewable energy. In this paper, a multi-time scale power load forecasting method based on wavelet threshold denoising and Prophet is proposed. Firstly, the wavelet threshold denoising algorithm is used to de-noise the historical load data to reduce the influence of inherent noise caused by acquisition equipment and transmission equipment on the results. Then the Prophet algorithm is used to build a time series model of historical data, so as to predict the future power load. This method can predict the power load at different time scales according to different demands. Simulation results show that the proposed method has high prediction accuracy and stable prediction results for different time scales.