Deep Reinforcement Learning for Voltage Control and Renewable Accommodation Using Spatial-Temporal Graph Information-Reference-Cited by-同舟云学术

Deep Reinforcement Learning for Voltage Control and Renewable Accommodation Using Spatial-Temporal Graph Information

Author:

Li Jinhao¹^ORCID,Zhang Ruichang²,Wang Hao³^ORCID,Liu Zhi⁴^ORCID,Lai Hongyang⁵^ORCID,Zhang Yanru⁶^ORCID

Affiliation:

1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China

2. Department of Computer Science, University of Manchester, Manchester, U.K.

3. Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia

4. Department of Computer and Network Engineering, University of Electro-Communications, Chofu, Tokyo, Japan

5. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China

6. University of Electronic Science and Technology of China (UESTC), Chengdu, China

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Research and Development Fund

Australian Research Council

Discovery Early Career Researcher Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Renewable Energy, Sustainability and the Environment

Link

Reference49 articles.

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3. Climate change 2022: Mitigation of climate change;Shukla,2022

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