User-Level Large Scale Load Forecasting Based on GPU

Load forecasting is an essential part in power system management and planning. In recent years, more and more researchers started to focus on the behavior of terminal customers, trying to improve the accuracy of load forecasting. This paper proposes to use the neuron network model to predict each user’s load first, and then aggregate all the forecasting results to get higher-level prediction. In order to speed up the process, we also design a model based on CUDA. We conducted several experiments on real-world data (160 thousand consumers’ load profiles) and the results confirm the effectiveness and efficiency of our method.