Optimal Operable Power Flow: Sample-Efficient Holomorphic Embedding-Based Reinforcement Learning-Reference-Cited by-同舟云学术

Optimal Operable Power Flow: Sample-Efficient Holomorphic Embedding-Based Reinforcement Learning

Author:

Sayed Ahmed Rabee¹^ORCID,Zhang Xian¹^ORCID,Wang Guibin²^ORCID,Wang Cheng³^ORCID,Qiu Jing⁴^ORCID

Affiliation:

1. School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen, China

2. College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China

3. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China

4. School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

General Program of Foundation of Shenzhen Science and Technology Committee

Major Science and Technology Special Projects in Xinjiang Autonomous Region

Xinjiang Autonomous Region Key Research and Development Task Special

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

Reference43 articles.

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