Decision support for intelligent energy management in buildings using the thermal comfort model

Abstract

The main objective of this paper is to present a transparent Decision Support System (DSS) for the energy managers of buildings, which can assist them in setting indoor temperature set point, based on the feedback received by the occupants. Within the proposed DSS, the Thermal Comfort Validator (TCV) tool is introduced, a fully responsive and cross-platform web-app which exploits the Predicted Mean Vote comfort theory by considering real-time feedback of the occupants. The TCV facilitates the detection of the range of accepted temperature inside a building, by correlating “real” with “predicted” thermal comfort, to overcome the limits of the standardized approaches. The proposed system can reveal an important potential for achieving energy savings by means of dynamic event driven data collection and processing, while ensuring high levels of comfort.