An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings
It addresses the problem of optimal energy management in smart buildings for building operators, but the approach is incremental, combining existing MPC with known components.
This paper presents a Model Predictive Control strategy for cost-optimal operation of large-scale buildings with HVAC, photovoltaic generation, and storage, achieving computationally efficient solutions even for large instances. Performance is evaluated under uncertainties using realistic simulations.
This paper deals with the problem of cost-optimal operation of smart buildings that integrate a centralized HVAC system, photovoltaic generation and both thermal and electrical storage devices. Building participation in a Demand-Response program is also considered. The proposed solution is based on a specialized Model Predictive Control strategy to optimally manage the HVAC system and the storage devices under thermal comfort and technological constraints. The related optimization problems turn out to be computationally appealing, even for large-scale problem instances. Performance evaluation, also in the presence of uncertainties and disturbances, is carried out using a realistic simulation framework.