Abstract:
In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) ...Show MoreMetadata
Abstract:
In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyber-physical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning feedback load management program that can operate on top of the rules. We demonstrate via extensive simulations the effectiveness of the program for intelligent management of the heating, ventilating and air conditioning (HVAC) loads so as to exploit renewable energy sources, while taking into account human-related constraints like thermal comfort.
Date of Conference: 03-06 July 2017
Date Added to IEEE Xplore: 07 August 2017
ISBN Information:
Electronic ISSN: 1948-3457