An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings. (15th April 2019)

• Record Type: Journal Article
• Authors: Bianchini, Gianni; Casini, Marco; Pepe, Daniele; Vicino, Antonio; Zanvettor, Giovanni Gino
• Is Part Of: Applied energy. Volume 240(2019)
• Page Start: 327
• Page End: 340
• Publication Date: 2019-04-15
• Subjects: Smart buildings -- Energy management systems -- Model predictive control -- Demand-response -- Mathematical modeling -- Optimization; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.01.187
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: An MPC approach is devised for efficient management of building HVAC systems. Electrical and thermal storage, PV generation and demand-response are considered. A low-complexity two-stage optimization approach is introduced. The proposed method is suitable for application to large-scale buildings. The approach is robust against inaccurate forecasts of exogenous inputs. Abstract: 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.