Multi-Agent Collaborative Optimization in New Power Systems Driven by Integration of Evolutionary Game and Federated Learning

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Multi-Agent Collaborative Optimization in New Power Systems Driven by Integration of Evolutionary Game and Federated Learning

Intelligent Learning-Empowered Power Generation in New Power Systems | Updated：2026-07-24

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- Multi-Agent Collaborative Optimization in New Power Systems Driven by Integration of Evolutionary Game and Federated Learning
- CHENG Lefeng , SUN Runbao , NI Manqi , ZOU Tao , YU Tao , ZHANG Xiaoshun , WANG Huaizhi
- Power Generation Technology Vol. 47, Issue 3, Pages: 449-483(2026)
- Affiliations：
  1.School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, Guangdong Province, China
  2.School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, Guangdong Province, China
  3.Foshan Graduate School of Innovation, Northeastern University, Foshan 528300, Guangdong Province, China
  4.College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, China
- Author bio：
- Funds：
- DOI： 10.12096/j.2096-4528.pgt.260301
  CLC：
- Revised：2026-03-18 ，
- Accepted：
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