An Epistemic-Deontic-Axiologic (EDA) agent-based energy management system in office buildings

• Published in: Applied energy Vol. 205; pp. 440 - 452
• Main Authors: Jiang, Lai, Yao, Runming, Liu, Kecheng, McCrindle, Rachel
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2017
• Subjects: air conditioning; Building Energy Management System (BEMS); buildings; cooling systems; data collection; energy efficiency; Epistemic, Deontic, Axiologic (EDA) agent model; greenhouse gas emissions; heat; Rational agent; sensation; Support vector machine; support vector machines; United Kingdom; United Kingdom; Building Energy Management System (BEMS); Rational agent; Epistemic, Deontic, Axiologic (EDA) agent model; Support vector machine
• ISSN: 0306-2619; 1872-9118; 1872-9118
• DOI: 10.1016/j.apenergy.2017.07.081

•A novel multi-agent Building Energy Management Systems is developed.•The model meets dual-objectives of thermal comfort and energy efficiency of the HVAC systems.•The Epistemic-Deontic-Axiologic (EDA) agent model is applied to develop rational agents.•E-component, D-component and A-component based multi-agent framework is described in details.•The method could enhance the capacity of energy efficient intelligent control of the HVAC system. In the UK, buildings contribute about one third of the energy-related greenhouse gas emissions. Space heating and cooling systems are among the biggest energy consumers in buildings. This research aims to develop a novel Building Energy Management System (BEMS) to reduce the energy consumption of the heating, ventilation and air-conditioning (HVAC) system while fulfilling each occupant’ thermal comfort requirement. This paper presents a newly developed novel method, Epistemic-Deontic-Axiologic (EDA) Agent-based solution to support the Energy Management System meeting the dual targets of occupant thermal comfort and energy efficiency. The multi-agent solutions are applied to the BEMS. The problem decomposition method is used to define the architecture of the system. The Epistemic-Deontic-Axiologic (EDA) agent model is applied to develop the rational local and personal agents inside the system. These EDA-based agents select their optimal action plan by considering the occupants’ thermal sensations, their behavioural adaptations and the energy consumption of the HVAC system. The Newly-developed personal thermal sensation models and group-of-people-based thermal sensation models generated by support vector machine (SVM) based algorithms are applied to evaluate the occupants’ thermal sensations. These models are developed from the data collected in a real built environment. Simulation results prove that the newly-developed BEMS can help the HVAC system reduce the energy consumption by up to 10% while fulfilling the occupants’ thermal comfort requirements.