Smart Buildings, Smart Grid, Optimization, Model Predictive Control
This paper proposes and develops an occupancy-based control and optimization framework for reducing energy consumption and cost within the context of Buildings-to-Grid (BtG) integration. A mathematical framework of large-scale integration, control and optimization of solar powered buildings with battery energy storage system and the grid is proposed and demonstrated. Building MPC formulations are designed based on appropriately linearized large commercial building conditioning and battery system models. A high-level linearized grid distribution network is also developed via IEEE standard grid systems with 9, 14, and 30 buses. The final decentralized utility-scale BtG integrations with battery storages, photovoltaics generations, different grid systems, building occupancy simulators, and building HVAC system are conceptually designed and simulated. The results show that the integrated system can save up to 40% to 46% amount of energy/costs from building side and 90% amount of operation costs from grid side.