ED-DQN: An event-driven deep reinforcement learning control method for multi-zone residential buildings

Residential Heating, Ventilation, and Air conditioning (HVAC) systems are responsible for a significant amount of energy consumption, but their management is challenging due to the complexities of building thermodynamics and human activities. Reinforcement learning (RL) has been adopted to tackle th...

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Veröffentlicht in:	Building and environment Jg. 242; S. 110546
Hauptverfasser:	Fu, Qiming, Li, Zhu, Ding, Zhengkai, Chen, Jianping, Luo, Jun, Wang, Yunzhe, Lu, You
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.08.2023
Schlagworte:	Deep reinforcement learning Event-driven HVAC systems Multi-zone residential buildings Thermal comfort control Deep reinforcement learning Multi-zone residential buildings HVAC systems Event-driven Thermal comfort control
ISSN:	0360-1323
Online-Zugang:	Volltext
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