Reinforcement learning for energy conservation and comfort in buildings |
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Authors: | K Dalamagkidis D Kolokotsa K Kalaitzakis GS Stavrakakis |
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Affiliation: | 1. Computer Science and Engineering Department, University of South Florida, Tampa, FL, USA;2. Technical Educational Institute of Crete, Department of Natural Resources and Environment, Chania, Crete,Greece;3. Technical University of Crete, Department of Chania, Crete, Greece |
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Abstract: | 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. |
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Keywords: | Energy management Indoor environment Reinforcement learning Adaptive control Energy efficiency |
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