Power Supply Demand Prediction System for Utility Groups

The patent segments the utility customer group into individual customers, each with their own battery storage and power generation devices. By predicting supply and demand at the individual level and then aggregating, the system maintains prediction accuracy even as power accommodation between customers increases. This segmentation allows tracking of each customer's battery status independently, preventing the loss of predictive information.

The system implements feedback by continuously monitoring actual power supply and demand data, comparing it with predictions, and using this information to improve future predictions. The prediction unit receives feedback from measurement units that track battery stored power, power generation, and power consumption, enabling the system to maintain accuracy despite frequent power accommodation events.

The prediction unit serves multiple functions simultaneously: it predicts power supply from batteries, predicts power generation from renewable sources, predicts power consumption by customers, and aggregates these to predict overall supply and demand for the utility customer group. This multi-functionality reduces the need for separate specialized systems for each prediction task.

The patent combines individual customer predictions into a group-level prediction by aggregating the supply and demand data. This merging approach maintains the detailed information needed for accurate prediction while presenting a consolidated view that simplifies overall system management and reduces the complexity of coordinating multiple independent prediction systems.