Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management

Yuanzheng Li; Yong Zhao; Lei Wu; Zhigang Zeng

doi:10.1007/978-981-99-0799-1_11

Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management

Yuanzheng Li
, Yong Zhao
, Lei Wu
, Zhigang Zeng

Department of Electrical and Computer Engineering

Huazhong University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

5 Scopus citations

Abstract

In recent years, renewable energy (RE) has been widely deployed, such as wind power and photovoltaic. Unlike traditional energy, RE resources are usually distributed.

Original language	English
Title of host publication	Engineering Applications of Computational Methods
Pages	231-253
Number of pages	23
DOIs	https://doi.org/10.1007/978-981-99-0799-1_11
State	Published - 2023

Publication series

Name	Engineering Applications of Computational Methods
Volume	14
ISSN (Print)	2662-3366
ISSN (Electronic)	2662-3374

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1007/978-981-99-0799-1_11

Cite this

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title = "Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management",

abstract = "In recent years, renewable energy (RE) has been widely deployed, such as wind power and photovoltaic. Unlike traditional energy, RE resources are usually distributed.",

author = "Yuanzheng Li and Yong Zhao and Lei Wu and Zhigang Zeng",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.",

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T1 - Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management

AU - Li, Yuanzheng

AU - Zhao, Yong

AU - Wu, Lei

AU - Zeng, Zhigang

PY - 2023

Y1 - 2023

N2 - In recent years, renewable energy (RE) has been widely deployed, such as wind power and photovoltaic. Unlike traditional energy, RE resources are usually distributed.

AB - In recent years, renewable energy (RE) has been widely deployed, such as wind power and photovoltaic. Unlike traditional energy, RE resources are usually distributed.

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UR - https://www.scopus.com/pages/publications/85159142165#tab=citedBy

U2 - 10.1007/978-981-99-0799-1_11

DO - 10.1007/978-981-99-0799-1_11

M3 - Chapter

AN - SCOPUS:85159142165

T3 - Engineering Applications of Computational Methods

SP - 231

EP - 253

BT - Engineering Applications of Computational Methods

ER -

Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management

Abstract

Publication series

UN SDGs

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