Article ID: | iaor20173620 |
Volume: | 69 |
Issue: | 1 |
Start Page Number: | 45 |
End Page Number: | 67 |
Publication Date: | Sep 2017 |
Journal: | Journal of Global Optimization |
Authors: | Zhang Zhao, Yuan Jing, Tang Shaojie, Du Ding-zhu |
Keywords: | scheduling, combinatorial optimization, demand, behaviour, heuristics |
Home owners are typically charged differently when they consume power at different periods within a day. Specifically, they are charged more during peak periods. Thus, in this paper, we explore how scheduling algorithms can be designed to minimize the peak energy consumption of a group of homes served by the same substation. We assume that a set of demand/response switches are deployed at a group of homes to control the activities of different appliances such as air conditioners or electric water heaters in these homes. Given a set of appliances, each appliance is associated with its instantaneous power consumption and duration, our objective is to decide when to activate different appliances in order to reduce the peak power consumption. This scheduling problem is shown to be NP‐Hard. To tackle this problem, we propose a set of appliance scheduling algorithms under both offline and online settings. For the offline setting, we propose a constant ratio approximation algorithm (with approximation ratio