How good are learning-based control v.s. model-based control for load shifting? Investigations on a single zone building energy system

Both model predictive control (MPC) and deep reinforcement learning control (DRL) have been presented as a way to approximate the true optimality of a dynamic programming problem, and these two have shown significant operational cost saving potentials for building energy systems. However, there is s...

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Veröffentlicht in:	Energy (Oxford) Jg. 273; H. C; S. 127073
Hauptverfasser:	Fu, Yangyang, Xu, Shichao, Zhu, Qi, O’Neill, Zheng, Adetola, Veronica
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United Kingdom Elsevier Ltd 01.06.2023 Elsevier
Schlagworte:	Approximate dynamic programming problem Building energy and control system Deep reinforcement learning energy energy costs issues and policy Model predictive control operating costs Model predictive control Deep reinforcement learning Building energy and control system Approximate dynamic programming problem
ISSN:	0360-5442
Online-Zugang:	Volltext
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