Leveraging AI for Enhanced Power Systems Control: An Introductory Study of Model-Free DRL Approaches-Reference-Cited by-同舟云学术

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Leveraging AI for Enhanced Power Systems Control: An Introductory Study of Model-Free DRL Approaches

Published:2024 Issue: Volume:12 Page:98189-98206
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhou Yi¹,Zhou Liangcai¹,Yi Zhehan²^ORCID,Shi Di³^ORCID,Guo Mengjie⁴

Affiliation:

1. East China Branch of State Grid Corporation, Shanghai, China

2. CPS, Pleasanton, CA, USA

3. Klipsch School of Electrical and Computer Engineering, New Mexico State University, Las Cruces, NM, USA

4. Beijing QU Creative Technology Company Ltd., Beijing, China

Funder

State Grid Corporation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10583893.pdf?arnumber=10583893

Reference108 articles.

1. Deep RL-based Volt-VAR Control and Attack Resiliency for DER-integrated Distribution Grids

2. Scalable Deep Reinforcement Learning-based Volt-VAR Optimization in Distribution Systems: a Mean-field Approach

3. Volt-VAR Optimization in Distribution Networks Using Twin Delayed Deep Reinforcement Learning

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