Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets

Jinyu Liu; Hongye Guo; Yun Li; Qinghu Tang; Fuquan Huang; Tunan Chen; Haiwang Zhong

doi:10.35833/MPCE.2024.000811

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Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets

Original Paper | 更新时间：2025-07-30

- Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets
- “In the realm of electricity market bidding, a new framework has been proposed to enhance bidding flexibility and profits. Researchers have developed a method that fully integrates high-dimensional bids (HDBs) into reinforcement learning (RL) algorithms. By using a neural network supply function (NNSF) embedded in a Markov decision process (MDP), the approach increases bidding flexibility and profits, particularly in markets with renewable energy uncertainties.”
- Journal of Modern Power Systems and Clean Energy Vol. 13, Issue 4, Pages: 1373-1382(2025)
- 作者机构：
  
  State Key Laboratory of Power System Operation and Control, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
  Shenzhen Power Supply Co. Ltd., Shenzhen 518001, China
  Tsinghua Shenzhen International Graduate School, Shenzhen 518071, China
- 作者简介：
  
  Jinyu Liu received the B.S. degree from the Department of Electrical Engineering, Xi’an Jiaotong University, Xi’an, China, in 2023. He is currently working toward the Ph.D. degree at the Department of Electrical Engineering, Tsinghua University, Beijing, China. His research interests include electricity market and machine learning.e-mail: liu-jy23@mails.tsinghua.edu.cn
  Hongye Guo received the B.S. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China, in 2015 and 2020, respectively. He is currently an Assistant Professor with the Department of Electrical Engineering, Tsinghua University. His research interests include electricity market, demand-side flexibility, and application of artificial intelligence in power system.e-mail: hyguo@tsinghua.edu.cn
  Yun Li received the B.S. degree from North China Electric Power University, Beijing, China, in 2011, and the Ph.D degree from The University of Manchester, Manchester, UK, in 2015. He is currently working as Overseas Leading Technology Expert in Electric Power Dispatching & Control Center, Shenzhen Power Supply Co., Ltd., Shenzhen, China. His research interests include power system operation, analysis, and electricity market.e-mail: liyun@sz.csg.cn
  Qinghu Tang received the B.S. degree from the Department of Electrical Engineering, Tsinghua University, Beijing, China, in 2020, where he is currently working toward the Ph.D. degree. His research interests include electricity market, data-driven analysis, and application of machine learning.e-mail: tqh20@mails.tsinghua.edu.cn
  Fuquan Huang received the B.S. and M.S. degrees from South China University of Technology, Guangzhou, China, in 2000 and 2003, respectively. He is currently working as General Manager in the Electric Power Dispatching & Control Center, Shenzhen Power Supply Co., Ltd., Shenzhen, China. His research interests include power system operation, analysis, and protective relaying.e-mail: huangfuquan@sz.csg.cn
  Tunan Chen received the B.S. degree from Huazhong University of Science and Technology, Wuhan, China, in 2015, and the Ph.D. degree from Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China, in 2022. He is currently working as Joint-training Postdoc in Shenzhen Power Supply Co., Ltd., Shenzhen, China, and Tsinghua University, Beijing, China. His research interests include power system operation, electricity market, and fault diagnosis.e-mail: chentunan@sz.csg.cn
  Haiwang Zhong received the B.S. and Ph.D. degrees in electrical engineering from Tsinghua University, Beijing, China. He is currently an Associate Professor with the Department of Electrical Engineering, Tsinghua University. He is also the Director of the Energy Internet Trading and Operation Research Department, Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu, China. His research interests include power system operation and optimization, and electricity market.e-mail: zhonghw@tsinghua.edu.cn
- 基金信息：
- DOI：10.35833/MPCE.2024.000811
  CLC：
- Received：30 July 2024，
  
  Revised：2024-10-07，
  
  Accepted：02 December 2024，
  
  Online First：28 January 2025，
  
  Published：15 July 2025
- 稿件说明：
移动端阅览
Liu Jinyu,Guo Hongye,Li Yun,et al.Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets[J].Journal of Modern Power Systems and Clean Energy,2025,13(04):1373-1382.
DOI：

Liu Jinyu,Guo Hongye,Li Yun,et al.Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets[J].Journal of Modern Power Systems and Clean Energy,2025,13(04):1373-1382. DOI： 10.35833/MPCE.2024.000811.

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Reinforcement Learning Based Bidding Method with High-dimensional Bids in Electricity Markets

DOI：10.35833/MPCE.2024.000811