Energy-efficient control of thermal comfort in multi-zone residential HVAC via reinforcement learning

Energy-efficient control of thermal comfort in multi-zone residential HVAC via reinforcement learning

Energy efficient control of thermal comfort has been already an important part of residential heating, ventilation, and air conditioning (HVAC) systems. However, the optimisation of energy saving control for thermal comfort is not an easy task due to the complex dynamics of HVAC systems, the dynamic...

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Bibliographic Details
Main Authors: Zheng-Kai Ding, Qi-Ming Fu, Jian-Ping Chen, Hong-Jie Wu, You Lu, Fu-Yuan Hu
Format: Article
Language:English
Published: Taylor & Francis Group 2022-12-01
Series:Connection Science
Subjects:
reinforcement learning
deep reinforcement learning
multi-zone residential hvac
energy consumption
thermal comfort
Online Access:http://dx.doi.org/10.1080/09540091.2022.2120598
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http://dx.doi.org/10.1080/09540091.2022.2120598

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