Two-timescale autonomous energy management strategy based on multi-agent deep reinforcement learning approach for residential multicarrier energy system-Reference-Cited by-同舟云学术

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Two-timescale autonomous energy management strategy based on multi-agent deep reinforcement learning approach for residential multicarrier energy system

Published:2023-12 Issue: Volume:351 Page:121777
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Zhang Bin,Hu Weihao,Ghias Amer M.Y.M.,Xu Xiao,Chen Zhe

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference36 articles.

1. Incentive-based integrated demand response for multiple energy carriers under complex uncertainties and double coupling effects;Zheng;Appl Energy,2021

2. Techno-economic assessment of blue and green ammonia as energy carriers in a low-carbon future;Pozo;Energ Conver Manage,2022

3. Multiagent reinforcement learning for energy management in residential buildings;Ahrarinouri;IEEE Trans Industr Inform,2021

4. An online energy tool for sizing integrated PV-BESS systems for residential prosumers;Korjani;Appl Energy,2022

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