期刊
BUILDING AND ENVIRONMENT
卷 42, 期 7, 页码 2686-2698出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2006.07.010
关键词
energy management; indoor environment; reinforcement learning; adaptive control; energy efficiency
This paper deals with the issue of achieving comfort in buildings with minimal energy consumption. Specifically a reinforcement learning controller is developed and simulated using the Matlab/Simulink environment. The reinforcement learning signal used is a function of the thermal comfort of the building occupants, the indoor air quality and the energy consumption. This controller is then compared with a traditional on/off controller, as well as a Fuzzy-PD controller. The results show that, even after a couple of simulated years of training, the reinforcement learning controller has equivalent or better performance when compared to the other controllers. (c) 2006 Elsevier Ltd. All rights reserved.
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