Community Microgrid Scheduling Considering Building Thermal Dynamics Using a Deep Learning Approach
U.S. Department of Energy OSTI
This paper proposes a deep-learning-based scheduling approach for community microgrids that explicitly accounts for building thermal dynamics and customer comfort preferences. Traditional heating, ventilation, and air-conditioning (HVAC) scheduling models are NP-hard and scale poorly, especially for large systems wi…
microgridmarket-demandplanning-designproject-lifecycleasset-portfoliosystem-integration