This project assessed the performance and benefits of integrated solar photovoltaic, battery storage, and microgrid control technologies for small commercial buildings. A standard solution was developed in which solar + storage is improved with flexible load control to reduce capital, operating, and management costs while supporting distribution grid functions. While COVID-19 and other external factors constrained accomplishing the project’s full objectives, this solution establishes a basis to replicate for similar buildings across the state.
The project developed and validated the open building autonomous tuning system or OpenBATS, an open-source software employed to simulate operations at a field demonstration site. Artificial intelligence/machine language (AI/ML) data-based algorithm was added and trained to minimize cost. The electric bill and simulation results showed significant energy and demand charge reductions for three more rigorous control cases (compared to baseline). The operations optimization, however, using AI/ML offered a cost reduction only slightly better than that of simple rule-based controls.
