Optimization based load forecasting and demand management in smart building microgrids with Greylag Goose and Bi level graph models

Key Points

• Effective load forecasting enhances efficiency in smart building microgrids, ensuring optimal energy use.
• The study uses bi-level graph models to assess demand management strategies and optimize energy distribution.
• Optimization techniques applied in this context focus on balancing load demands and available resources in real-time.
• Findings suggest that these models may lead to cost savings and improved sustainability in building energy management.