New encoding method enhances demand prediction for renewable systems (IMAGE)
Caption
Researchers at Institute of Science Tokyo have developed a novel Group Encoding method that accurately forecasts electricity demand using only On/Off device data from building energy systems. Tested on real-world datasets, this technique improves forecasting accuracy by 74% compared to conventional methods, offering a scalable and low-cost solution for managing distributed energy systems and integrating renewable energy.
Credit
Institute of Science Tokyo
Usage Restrictions
For use in scientific news only. Attribution is required. The image may not be modified in ways that alters its meaning or context.
License
Original content