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Energies 2017, 10(3), 321;

An Economic Model-Based Predictive Control to Manage the Users’ Thermal Comfort in a Building

Department of Informatics, University of Almería, Agrifood Campus of International Excellence (ceiA3) CIESOL Joint Centre University of Almería—CIEMAT, 04120 Almería, Spain
Department of System Engineering and Automation, School of Engineering, University of Seville, 41092 Seville, Spain
Faculty of Science and Technology, University of Algarve, Faro, Portugal and, IDMEC, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal
Author to whom correspondence should be addressed.
Academic Editor: Giovanni Pau
Received: 2 December 2016 / Revised: 16 February 2017 / Accepted: 2 March 2017 / Published: 7 March 2017
(This article belongs to the Special Issue Smart Home Energy Management)
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The goal of maintaining users’ thermal comfort conditions in indoor environments may require complex regulation procedures and a proper energy management. This problem is being widely analyzed, since it has a direct effect on users’ productivity. This paper presents an economic model-based predictive control (MPC) whose main strength is the use of the day-ahead price (DAP) in order to predict the energy consumption associated with the heating, ventilation and air conditioning (HVAC). In this way, the control system is able to maintain a high thermal comfort level by optimizing the use of the HVAC system and to reduce, at the same time, the energy consumption associated with it, as much as possible. Later, the performance of the proposed control system is tested through simulations with a non-linear model of a bioclimatic building room. Several simulation scenarios are considered as a test-bed. From the obtained results, it is possible to conclude that the control system has a good behavior in several situations, i.e., it can reach the users’ thermal comfort for the analyzed situations, whereas the HVAC use is adjusted through the DAP; therefore, the energy savings associated with the HVAC is increased. View Full-Text
Keywords: thermal comfort; energy efficiency; Predicted Mean Vote index; economic MPC thermal comfort; energy efficiency; Predicted Mean Vote index; economic MPC

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Alamin, Y.I.; Castilla, M.M.; Álvarez, J.D.; Ruano, A. An Economic Model-Based Predictive Control to Manage the Users’ Thermal Comfort in a Building. Energies 2017, 10, 321.

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