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Article

Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances

School of Electrical and Electronics Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Korea
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Sensors 2019, 19(18), 3937; https://doi.org/10.3390/s19183937
Received: 13 August 2019 / Revised: 9 September 2019 / Accepted: 9 September 2019 / Published: 12 September 2019
(This article belongs to the Special Issue Home Automation for the Internet of Things)
This paper presents a data-driven approach that leverages reinforcement learning to manage the optimal energy consumption of a smart home with a rooftop solar photovoltaic system, energy storage system, and smart home appliances. Compared to existing model-based optimization methods for home energy management systems, the novelty of the proposed approach is as follows: (1) a model-free Q-learning method is applied to energy consumption scheduling for an individual controllable home appliance (air conditioner or washing machine), as well as the energy storage system charging and discharging, and (2) the prediction of the indoor temperature using an artificial neural network assists the proposed Q-learning algorithm in learning the relationship between the indoor temperature and energy consumption of the air conditioner accurately. The proposed Q-learning home energy management algorithm, integrated with the artificial neural network model, reduces the consumer electricity bill within the preferred comfort level (such as the indoor temperature) and the appliance operation characteristics. The simulations illustrate a single home with a solar photovoltaic system, an air conditioner, a washing machine, and an energy storage system with the time-of-use pricing. The results show that the relative electricity bill reduction of the proposed algorithm over the existing optimization approach is 14%. View Full-Text
Keywords: home energy management system; reinforcement learning; artificial neural network; smart home; consumer comfort; smart grid home energy management system; reinforcement learning; artificial neural network; smart home; consumer comfort; smart grid
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MDPI and ACS Style

Lee, S.; Choi, D.-H. Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances. Sensors 2019, 19, 3937. https://doi.org/10.3390/s19183937

AMA Style

Lee S, Choi D-H. Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances. Sensors. 2019; 19(18):3937. https://doi.org/10.3390/s19183937

Chicago/Turabian Style

Lee, Sangyoon, and Dae-Hyun Choi. 2019. "Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances" Sensors 19, no. 18: 3937. https://doi.org/10.3390/s19183937

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