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 | 更新时间：2026-07-24

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- Multi-Agent Collaborative Optimization in New Power Systems Driven by Integration of Evolutionary Game and Federated Learning
- 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
- 发电技术（英文版） 2026年47卷第3期页码：449-483
- 作者机构：
  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
- 作者简介：
- 基金信息：
  National Natural Science Foundation of China(52171331;U24B6010);Natural Science Foundation of Guangdong Province(2023A1515011311);Innovation Team Project for Ordinary Universities in Guangdong Province(2024KCXTD031);Guangzhou Education Bureau University Research Project(2024312278)
- DOI： 10.12096/j.2096-4528.pgt.260301
  中图分类号：
- 修回：2026-03-18 ，
- 稿件说明：
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