Multi-agent control system with intelligent optimisation for building energy and comfort management. (2016)

• Record Type: Journal Article
• Authors: Kan, Ee May; Kan, Siew Leong; Soh, Yvonne; Zi, Dou; Yadanar, Khaing
• Is Part Of: International journal of automation and logistics. Volume 2:Number 1/2(2016)
• Page Start: 60
• Page End: 77
• Publication Date: 2016
• Subjects: multi-agent control -- computational intelligence -- multi-agent systems -- MAS -- agent-based systems -- intelligent optimisation -- building energy management -- building comfort management -- smart buildings -- sustainable buildings -- energy efficiency -- green buildings -- energy consumption -- occupant comfort levels -- heating ventilation air-conditioning -- HVAC; Automation -- Periodicals; Logistics -- Periodicals; Logistics -- Computer programs -- Periodicals; 658.514
• Languages: English
• ISSNs: 2049-6745

Abstract

Smart, sustainable and energy-efficient buildings have recently become a trend for intelligent and green building industry. One of the challenges for such a building is to minimise power consumption without compromising the occupant comfort. It is possible to sustain high comfort level with minimal energy consumption through intelligent multi-agent control and optimisation. Our work focuses on a new algorithmic aspect that makes buildings more intelligent, resource efficient and comfortable for occupants. A multi-agent control system with intelligent optimisation is proposed to optimise heating, ventilation and air-conditioning (HVAC) processes using computational intelligence approaches. The optimum solutions generated through the optimisation engine and task scheduling for each agent will be used to sustain a high level of occupant comfort with minimal power consumption, increase energy utilisation efficiency, and consequently reduce energy cost. Experimental results and comparisons with other evolutionary approaches demonstrate the overall performance and potential benefits of the new framework.