Advanced control systems engineering for energy and comfort management in a building environment—A review

• Published in: Renewable & sustainable energy reviews Vol. 13; no. 6; pp. 1246 - 1261
• Main Authors: Dounis, A.I., Caraiscos, C.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-08-2009; Elsevier
• Series: Renewable and Sustainable Energy Reviews
• Subjects: Ambient intelligence; Applied sciences; Building energy management system; Controller-agent Ambient intelligence Multi-agent control system Building energy management system Fuzzy PID Optimization techniques; Controller–agent; Energy; Energy. Thermal use of fuels; Exact sciences and technology; Fuzzy PID; Heating, air conditioning and ventilation; Multi-agent control system; Optimization techniques; Technical data: comfort, insulation, loads, etc; Optimization techniques; Controller–agent; Building energy management system; Ambient intelligence; Fuzzy PID; Multi-agent control system; Thermal comfort; Fuzzy system; Buildings; Evolutionary algorithm; Control system; Review; Neural network; Multiagent system; Energy management; Artificial intelligence; Controller-agent
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2008.09.015

Given restrictions that comfort conditions in the interior of a building are satisfied, it becomes obvious that the problem of energy conservation is a multidimensional one. Scientists from a variety of fields have been working on this problem for a few decades now; however, essentially it remains an open issue. In the beginning of this article, we define the whole problem in which the topics are: energy, comfort and control. Next, we briefly present the conventional control systems in buildings and their advantages and disadvantage. We will also see how the development of intelligent control systems has improved the efficiency of control systems for the management of indoor environment including user preferences. This paper presents a survey exploring state of the art control systems in buildings. Attention will be focused on the design of agent-based intelligent control systems in building environments. In particular, this paper presents a multi-agent control system (MACS). This advanced control system is simulated using TRNSYS/MATLAB. The simulation results show that the MACS successfully manage the user’s preferences for thermal and illuminance comfort, indoor air quality and energy conservation.