Optimal operation of regional integrated energy system based on multi-agent deep deterministic policy gradient algorithm

The complex energy coupling and uncertainties of renewable energy and load make the dynamic scheduling of the integrated energy system (IES) very difficult. Therefore, an optimal operation method based on the multi-agent deep deterministic policy gradient algorithm (MADDPG) is proposed. Firstly, the...

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Bibliographic Details
Published in:	Energy reports Vol. 8; pp. 932 - 939
Main Authors:	Xu, Bohan, Xiang, Yue
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.11.2022 Elsevier
Subjects:	Deep deterministic policy gradient algorithm Integrated energy system Multi-agent scheduling Integrated energy system Deep deterministic policy gradient algorithm Multi-agent scheduling
ISSN:	2352-4847, 2352-4847
Online Access:	Get full text
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Summary:	The complex energy coupling and uncertainties of renewable energy and load make the dynamic scheduling of the integrated energy system (IES) very difficult. Therefore, an optimal operation method based on the multi-agent deep deterministic policy gradient algorithm (MADDPG) is proposed. Firstly, the IES model is established, and the optimal scheduling problem is transformed into the Markov decision problem; Then, the action-space, state-space and reward function of agents are designed which control energy conversion equipment and energy storage equipment respectively. Furtherly, a multi-agent framework is established based on the MADDPG; Finally, a scheduling simulation example was carried out. The simulation results indicate that compared with the single agent, the multi-agent framework can improve the stability of training for agents and the ability to explore the optimal solution.
ISSN:	2352-4847 2352-4847
DOI:	10.1016/j.egyr.2022.08.066