Energy Regulation-Aware Layered Control Architecture for Building Energy Systems Using Constraint-Aware Deep Reinforcement Learning and Virtual Energy Storage Modeling

In modern intelligent buildings, the control of Building Energy Systems (BES) faces increasing complexity in balancing energy costs, thermal comfort, and operational flexibility. Traditional centralized or flat deep reinforcement learning (DRL) methods often fail to effectively handle the multi-time...

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Bibliographic Details

Published in:	Energies
Main Authors:	Siwei Li, Congxiang Tian, Ahmed N. Abdalla
Format:	Article
Language:	English
Published:	MDPI AG 2025-09-01
Subjects:	building energy system reinforcement learning Markov decision process virtual energy storage policy regulation deep reinforcement learning
Online Access:	https://www.mdpi.com/1996-1073/18/17/4698