LGA-based short-term power load time series forecasting

Accurate power load forecasting is crucial to decide on the power grid's operation and customers' power consumption management. It can ensure the power system's reliable power supply and the grid economy's reliable operation. However, as population and electricity consumption continues to increase, the power system poses a huge challenge. Accurate power load forecasting is an effective way to solve the problem. Therefore, this paper proposes a short-term power timing prediction model based on LGA. First, the power data is fed into LSTM and GRU to improve the model robustness in a parallel way. Second, the output results of LSTM and GRU are weighted and summed to obtain the output results by the activation function. After experimental validation with separate RNN, LSTM, and GRU, the model in this paper has high prediction performance.