A fast and accurate multi-user load forecasting method based on coupled traditional neural networks and a time-series large model

Key Points

• The proposed method provides accurate load forecasting, improving prediction reliability for multiple users.
• An accuracy rate of approximately 95% was achieved through this innovative approach involving neural networks.
• Analysis employs coupled traditional neural networks alongside a large time-series model for enhanced performance.
• This approach highlights the necessity for fast and precise load forecasting in multi-user environments.