Το work with title Reinforcement learning for energy conservation and comfort in buildings by Dalamagkidis, K, Kolokotsa Dionysia, Kalaitzakis Kostas, Stavrakakis Georgios is licensed under Creative Commons Attribution 4.0 International
Bibliographic Citation
K. Dalamagkidis, D. Kolokotsa, K. Kalaitzakis, and G.S. Stavrakakis, "Reinforcement learning for energy conservation and comfort in buildings," Building and Environment, vol. 42, no. 7, pp. 2686–2698, Jul. 2007. doi:10.1016/j.buildenv.2006.07.010
https://doi.org/10.1016/j.buildenv.2006.07.010
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.