Online Preventive Control for Transmission Overload Relief Using Safe Reinforcement Learning With Enhanced Spatial-Temporal Awareness-Reference-Cited by-同舟云学术

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Online Preventive Control for Transmission Overload Relief Using Safe Reinforcement Learning With Enhanced Spatial-Temporal Awareness

Published:2024-01 Issue:1 Volume:39 Page:517-532
ISSN:0885-8950
Container-title:IEEE Transactions on Power Systems
language:
Short-container-title:IEEE Trans. Power Syst.

Author:

Cui Han¹^ORCID,Ye Yujian²^ORCID,Hu Jianxiong²^ORCID,Tang Yi²^ORCID,Lin Zizhao³,Strbac Goran⁴

Affiliation:

1. School of Cyber Science and Engineering, Southeast University, Nanjing, China

2. School of Electrical Engineering, Southeast University, Nanjing, China

3. Shenzhen Power Supply Bureau, Shenzhen, China

4. Department of Electrical and Electronic Engineering, Imperial College London, London, U.K.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Shuangchuang Program of Jiangsu Province

China Southern Power Grid Shenzhen Power Supply Bureau

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

http://xplorestaging.ieee.org/ielx7/59/10375287/10070802.pdf?arnumber=10070802

Reference65 articles.

1. Net zero by 2050,2021

2. Optimal Operation of an Integrated Electricity-heat Energy System Considering Flexible Resources Dispatch for Renewable Integration

3. Transmission Line Overload Risk Assessment for Power Systems With Wind and Load-Power Generation Correlation

4. A survey on recent advances in transmission congestion management

5. Multi-Objective based Congestion Management using Generation Rescheduling and Load Shedding

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced feature combinational optimization for multivariate time series based dynamic early warning in power systems;Expert Systems with Applications;2024-10

2. Deep Reinforcement Learning for Smart Grid Operations: Algorithms, Applications, and Prospects;Proceedings of the IEEE;2023-09

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