Research on Reactive Power Optimization of Active Distribution Network Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Research on Reactive Power Optimization of Active Distribution Network Based on Deep Reinforcement Learning

Published:2023-08 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd Power System and Green Energy Conference (PSGEC)
language:
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Author:

Cai Changchun¹,Liu Jingna²,Wang Yuanyuan³,Li Yuanjia²,Fan Jinghao²,He Jie²

Affiliation:

1. Hohai University,Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology,Changzhou,China

2. College of Information Sciences and Engineering, Hohai University,Changzhou,China

3. Dongying Power Supply Company, State Grid Shandong Electric Power Company,Dongying,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10255721/10255807/10255927.pdf?arnumber=10255927

Reference8 articles.

1. A PMU-Based Data-Driven Approach for Enhancing Situational Awareness in Building A Resilient Power Systems

2. Adaptive Power System Emergency Control Using Deep Reinforcement Learning

3. Two-Timescale Voltage Control in Distribution Grids Using Deep Reinforcement Learning

4. Definition and Classification of Power System Stability – Revisited & Extended

5. Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning

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