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A Fuzzy-Based Building Energy Management System for Energy Efficiency

Fundación CARTIF, Energy division, 47151 Boecillo, Spain
Acciona R+D, 41012 Sevilla, Spain
Acciona Construcción, 28108 Madrid, Spain
Authors to whom correspondence should be addressed.
This text has been expanded from an original conference paper.
Buildings 2018, 8(2), 14;
Received: 22 September 2017 / Revised: 19 January 2018 / Accepted: 22 January 2018 / Published: 25 January 2018
(This article belongs to the Special Issue Selected Papers from Sustainable Places 2017 (SP2017) Conference)
PDF [883 KB, uploaded 25 January 2018]


Information and communication technologies (ICT) offer immense potential to improve the energetic performance of buildings. Additionally, common building control systems are typically based on simple decision-making tools, which possess the ability to obtain controllable parameters for indoor temperatures. Nevertheless, the accuracy of such common building control systems is improvable with the integration of advanced decision-making techniques embedded into software and energy management tools. This paper presents the design of a building energy management system (BEMS), which is currently under development, and that makes use of artificial intelligence for the automated decision-making process required for optimal comfort of occupants and utilization of renewables for achieving energy-efficiency in buildings. The research falls under the scope of the H2020 project BREASER which implements fuzzy logic with the aim of governing the energy resources of a school in Turkey, which has been renovated with a ventilated façade with integrated renewable energy sources (RES). The BRESAER BEMS includes prediction techniques that increase the accuracy of common BEMS tools, and subsequent energy savings, while ensuring the indoor thermal comfort of the building occupants. In particular, weather forecast and simulation strategies are integrated into the functionalities of the overall system. By collecting the aforementioned information, the BEMS makes decisions according to a well-established selection of key performance indicators (KPIs) with the objective of providing a quantitative comparable value to determine new actuation parameters. View Full-Text
Keywords: building energy management system (BEMS); monitoring and control; data analytics; key performance indicators (KPIs); decision-making tools; fuzzy logic; artificial intelligence building energy management system (BEMS); monitoring and control; data analytics; key performance indicators (KPIs); decision-making tools; fuzzy logic; artificial intelligence

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Hernández, J.L.; Sanz, R.; Corredera, Á.; Palomar, R.; Lacave, I. A Fuzzy-Based Building Energy Management System for Energy Efficiency. Buildings 2018, 8, 14.

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