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Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Deep reinforcement learning based reactive power regulation and its optimization in power grids
Yi Zhou
Yi Zhou
East China Branch of State Grid Corporation
Shanghai, China
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Zhou, Yi
,
Liangcai Zhou
Liangcai Zhou
East China Branch of State Grid Corporation
Shanghai, China
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Zhou, Liangcai
,
Xu Sheng
Xu Sheng
NARI Group Corporation (State Grid Electric Power Research Institute)
Nanjing, China
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Sheng, Xu
,
Dongjian Gu
Dongjian Gu
NARI Group Corporation (State Grid Electric Power Research Institute)
Nanjing, China
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Gu, Dongjian
,
Weijian Shen
Weijian Shen
NARI Group Corporation (State Grid Electric Power Research Institute)
Nanjing, China
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Shen, Weijian
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Qing Chen
Qing Chen
NARI Group Corporation (State Grid Electric Power Research Institute)
Nanjing, China
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Chen, Qing
Nov 05, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
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Published Online:
Nov 05, 2024
Received:
Jun 03, 2024
Accepted:
Sep 30, 2024
DOI:
https://doi.org/10.2478/amns-2024-3041
Keywords
Deep reinforcement learning
,
HAPPPO algorithm
,
Markov decision making
,
Grid power regulation
© 2024 Yi Zhou et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
