TY - CHAP
T1 - Federated Multi-agent Deep Reinforcement Learning for Multi-microgrid Energy Management
AU - Li, Yuanzheng
AU - Zhao, Yong
AU - Wu, Lei
AU - Zeng, Zhigang
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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.
UR - http://www.scopus.com/inward/record.url?scp=85159142165&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85159142165&partnerID=8YFLogxK
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 -