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http://dx.doi.org/10.7471/ikeee.2022.26.1.56

Reinforcement Learning-Based Illuminance Control Method for Building Lighting System  

Kim, Jongmin (Dept. of Software, Dongseo University)
Kim, Sunyong (Dept. of Software, Dongseo University)
Publication Information
Journal of IKEEE / v.26, no.1, 2022 , pp. 56-61 More about this Journal
Abstract
Various efforts have been made worldwide to respond to environmental problems such as climate change. Research on artificial intelligence (AI)-based energy management has been widely conducted as the most effective way to alleviate the climate change problem. In particular, buildings that account for more than 20% of the total energy delivered worldwide have been focused as a target for energy management using the building energy management system (BEMS). In this paper, we propose a multi-armed bandit (MAB)-based energy management algorithm that can efficiently decide the energy consumption level of the lighting system in each room of the building, while minimizing the discomfort levels of occupants of each room.
Keywords
Reinforcement learning; multi-armed bandit; building energy management; lighting system; illuminance control; user's discomfort;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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