Electric load forecasting (ELF) is always employed to perform power systems management. However, it is difficult to predict electric load due to the following issues: 1) electric load prediction is prone to external interference, e.g., temperature and weather; 2) the user behaviors are random, such as family gatherings and business rush orders; and 3) electric load consumption varies significantly in different time periods. To solve such problems, an adaptive sparse attention network (ASA-Net) is proposed for ELF, where the adaptive sparse spatial attention (ASSA) module is first designed to i...
