Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method

Chenxu Yin; Yonghui Sun; Dongliang Xie; Fan Sheng; Liang Zhao

doi:10.35833/MPCE.2025.000695

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Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method

Original Paper | 更新时间：2026-09-28

- Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method
- Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method
- MPCE 2026年14卷第5期页码：1720-1731
- 作者机构：
  
  1.School of Electrical and Power Engineering, Hohai University, Nanjing 210098, China
  2.State Grid Electric Power Research Institute, Nanjing 211106, China
- 作者简介：
  
  Chenxu Yin is currently pursuing the Ph.D. degree in electrical engineering from Hohai University, Nanjing, China. His research interests include multi-energy system, collaborative optimization, game theory, and convex optimization. Email:chen_xu_yin@163.com
  Yonghui Sun received the Ph.D. degree from the City University of Hong Kong, Hong Kong, China, in 2010. He is currently a Professor with the School of Electrical and Power Engineering, Hohai University, Nanjing, China. His research interests include stability analysis and control of power systems, optimal planning and operation of integrated energy systems, optimization algorithm, and data analysis. Email:sunyonghui168@gmail.com
  Dongliang Xie received the Ph.D. degree in electrical engineering from Southeast University, Nanjing, China, in 2012. During 2011-2012, he was a Research Associate in Hong Kong Polytechnic University, Hong Kong, China. He is currently working for State Grid Electric Power Research Institute (SGEPRI), Nanjing, China. His research interests include digital-twin platform of complex systems, planning and operation optimization for high-renewable-penetration power systems, and resilience analysis under extreme cases. Email:xiedongliang@sgepri.sgcc.com.cn
  Fan Sheng is currently pursuing the M.S. degree in electrical engineering from Hohai University, Nanjing, China. His research interests include integrated energy system and robust optimization. Email:sf_011106@163.com
  Liang Zhao is currently pursuing the Ph.D. degree in electrical engineering from Hohai University, Nanjing, China. His research interests include analysis of power system adequacy, collaborative optimization, backup optimization, and deep reinforcement learning. Email:zhaoliang3626@163.com
- 基金信息：
  
  the Science and Technology Project of NARI Technology Co., Ltd. “Interaction and Coordination Technology of Information-Physical-Social Elements”(GF-GFWD-210338)
- DOI：10.35833/MPCE.2025.000695
  中图分类号：
- 收稿：2025-07-29，
  
  修回：2025-11-01，
  
  录用：2026-02-13，
  
  网络首发：2026-03-30，
  
  纸质出版：2026-09-15
- 稿件说明：
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Chenxu Yin, Yonghui Sun, Dongliang Xie, 等. Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method[J]. MPCE, 2026,14(5):1720-1731.

Yin Chenxu,Sun Yonghui,Xie Dongliang,et al.Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1720-1731.
Chenxu Yin, Yonghui Sun, Dongliang Xie, 等. Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method[J]. MPCE, 2026,14(5):1720-1731. DOI： 10.35833/MPCE.2025.000695.

Yin Chenxu,Sun Yonghui,Xie Dongliang,et al.Non-cooperative Game Optimization of Urban Energy Systems Based on Inner-outer Iterative Method[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1720-1731. DOI： 10.35833/MPCE.2025.000695.

摘要

Abstract

This paper addresses the increasingly tight energy coupling in urban energy systems

which are composed of the power distribution network (PDN)

the transportation network (TN)

and the gas distribution network (GDN). A non-cooperative game optimization model for the urban energy system is developed

to achieve coordinated optimization among these three different energy networks operated by independent stakeholders. To avoid excessive sharing of private information

an inner-outer iterative method is further proposed to obtain the Nash equilibrium and enhance solving efficiency. In the proposed method

each energy network is iteratively optimized by exchanging only the price and load information

and the network parameters are not disclosed. In the inner layer

the PDN-TN coupled subsystem and the PDN-GDN coupled subsystem are solved separately. In the outer layer

interactions between charging loads and gas prices are coordinated through the PDN

thereby enabling cross-network coordination of urban energy systems. Case studies demonstrate that the convergence speed of the PDN-TN coupled subsystem is significantly improved by dynamically adjusting the electricity price based on sensitivity coefficients. Balanced resource allocation of the urban energy system is achieved through the non-cooperative game

while autonomy of all stakeholders is preserved. Energy procurement costs are reduced by up to 25.56% compared with that of the PDN-TN coupled subsystem.

关键词

Keywords

references

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