Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors

Zhi Rui; Xiaoyuan Xu; Zheng Yan; Bin Qian; Xiaoming Lin

doi:10.35833/MPCE.2025.000941

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors

Original Paper | 更新时间：2026-09-28

- Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors
- Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors
- MPCE 2026年14卷第5期页码：1732-1743
- 作者机构：
  
  1.Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Shanghai Jiao Tong University), , Shanghai 200240, China
  2.Shanghai Non-carbon Energy Conversion and Utilization Institute, Shanghai 200240, China
  3.Electric Power Research Institute of China Southern Power Grid, Guangzhou 510663, China
  4.Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid, Guangzhou 510663, China
- 作者简介：
  
  Zhi Rui received the B.S. degree in electrical engineering and automation from Chongqing University, Chongqing, China, in 2019, and the M.S. degree in electrical engineering from Shanghai Jiao Tong University, Shanghai, China, in 2022. He is currently pursuing a Ph.D. degree in electrical engineering at Shanghai Jiao Tong University. His research interests include power system optimization and power network resilience. Email:ruizhi1996@sjtu.edu.cn
  Xiaoyuan Xu received the B.S. and Ph.D. degrees in electrical engineering from Shanghai Jiao Tong University, Shanghai, China, in 2010 and 2016, respectively. He is currently an Associate Professor of electrical engineering at Shanghai Jiao Tong University. His research interests include power system uncertainty analysis and optimization. Email:xuxiaoyuan@sjtu.edu.cn
  Zheng Yan received the B.S. degree from Shanghai Jiao Tong University, Shanghai, China, in 1984, and the M.S. and Ph.D. degrees from Tsinghua University, Beijing, China, in 1987 and 1991, respectively, all in electrical engineering. He is currently a Professor of electrical engineering at Shanghai Jiao Tong University. His current research interests include application of optimization theory to power system, electricity market, and dynamic security assessment. Email:yanz@sjtu.edu.cn
  Bin Qian received the master’s degree in electrical engineering from Huazhong University of Science and Technology, Wuhan, China. He is currently the Head of the Measurement Equipment and Test Laboratory of Measurement Research Institute, Electric Power Research Institute of China Southern Power Grid, Guangzhou, China. His main research interests include electrical measurement and intelligent equipment detection. Email:qianbin@csg.cn
  Xiaoming Lin received the M.S. degree from South China University of Technology, Guangzhou, China. He is currently a Researcher at the Electric Power Research Institute of China Southern Power Grid, Guangzhou, China. His research interest includes interaction between electric vehicle and power grid. Email:linxm4@csg.cn
- 基金信息：
  
  Digital Grid Research Foundation of China Southern Power Grid(DPGCSG-2024-KF-19)
- DOI：10.35833/MPCE.2025.000941
  中图分类号：
- 收稿：2025-10-03，
  
  修回：2026-01-07，
  
  录用：2026-03-22，
  
  网络首发：2026-04-29，
  
  纸质出版：2026-09-15
- 稿件说明：
移动端阅览
Zhi Rui, Xiaoyuan Xu, Zheng Yan, 等. Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors[J]. MPCE, 2026,14(5):1732-1743.

Rui Zhi,Xu Xiaoyuan,Yan Zheng,et al.Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1732-1743.
Zhi Rui, Xiaoyuan Xu, Zheng Yan, 等. Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors[J]. MPCE, 2026,14(5):1732-1743. DOI： 10.35833/MPCE.2025.000941.

Rui Zhi,Xu Xiaoyuan,Yan Zheng,et al.Risk Assessment of Coupled Transportation Network and Distribution Network Considering Charging Power Restriction and Uncertainty Factors[J].Journal of Modern Power Systems and Clean Energy,2026,14(05):1732-1743. DOI： 10.35833/MPCE.2025.000941.

摘要

Abstract

The increasing interdependence between transportation networks (TNs) and distribution networks (DNs) presents significant challenges for the analysis and risk assessment of coupled networks. This paper presents a risk assessment framework of coupled TN and DN (TDN) considering charging power restriction and uncertainty factors

simulating operations through a coordinated optimization model. The model incorporates charging power restrictions for fast charging stations (FCSs). To enhance computation efficiency

nonlinear constraints are linearized

and an accuracy-aware adaptive piecewise linearization method is utilized. Random variables within the coupled TDN are employed as inputs to develop a surrogate model based on the Gaussian process regression method

complemented by suitable kernel functions designed for the scenarios with numerous discrete categorical variables. A global sensitivity analysis is conducted to identify the continuous and discrete uncertainty factors that significantly impact system performance. The proposed risk assessment framework serves as a valuable tool for evaluating the coupled TDN and facilitating the identification of continuous and discrete uncertainty factors affecting network operation while revealing risks associated with failures in the operation of coupled TDN.

关键词

Keywords

references

S. Chen, H. Cheng, S. Lv et al ., “Learning-aided collaborative optimization of power, hydrogen, and transportation networks,” Journal of Modern Power Systems and Clean Energy , vol. 13 , no. 2 , pp. 475 - 487 , Mar. 2025 .

K. Hou, X. Xu, H. Jia et al. , “A reliability assessment approach for integrated transportation and electrical power systems incorporating electric vehicles,” IEEE Transactions on Smart Grid , vol. 9 , no. 1 , pp. 88 - 100 , Jan. 2018 .

Q. Zhang, Y. Zhu, Z. Wang et al. , “Reliability assessment of distribution network and electric vehicle considering quasi-dynamic traffic flow and vehicle-to-grid,” IEEE Access , vol. 7 , pp. 131201 - 131213 , Jul. 2019 .

H. Wang, Y. Fang, and E. Zio, “Risk assessment of an electrical power system considering the influence of traffic congestion on a hypothetical scenario of electrified transportation system in new york state,” IEEE Transactions on Intelligent Transportation Systems , vol. 22 , no. 1 , pp. 142 - 155 , Jan. 2021 .

N. Liu, X. Hu, L. Ma et al. , “Vulnerability assessment for coupled network consisting of power grid and EV traffic network,” IEEE Transactions on Smart Grid , vol. 13 , no. 1 , pp. 589 - 598 , Jan. 2022 .

Y. Li, D. Zhang, J. Zhu et al. , “Resilience enhancement in urban power-transportation system considering multiple uncertainties against ice storms,” IEEE Transactions on Smart Grid , vol. 16 , no. 1 , pp. 801 - 815 , Jan. 2025 .

H. Wang, X. Xu, Y. Chen et al. , “Stochastic optimization of coupled power distribution-urban transportation network operations with autonomous mobility on demand systems,” IEEE Transactions on Smart Grid , vol. 15 , no. 3 , pp. 3040 - 3053 , May 2024.

W. Zuo, K. Li, and J. Zhong, “Reliability assessment of power supply systems integrated with renewables for electric road system,” Journal of Modern Power Systems and Clean Energy , vol. 13 , no. 4 , pp. 1300 - 1309 , Jul. 2025 .

K. Cheng, Z. Lu, C. Ling et al. , “Surrogate-assisted global sensitivity analysis: an overview,” Structural and Multidisciplinary Optimization , vol. 61 , no. 3 , pp. 1187 - 1213 , Mar. 2020 .

G. Ökten and Y. Liu, “Randomized quasi-monte carlo methods in global sensitivity analysis,” Reliability Engineering & System Safety , vol. 210 , p. 107520 , Jun. 2021 .

H. Sheng and X. Wang, “Applying polynomial chaos expansion to assess probabilistic available delivery capability for distribution networks with renewables,” IEEE Transactions on Power Systems , vol. 33 , no. 6 , pp. 6726 - 6735 , Nov. 2018 .

X. Wang, X. Wang, H. Sheng et al. , “A data-driven sparse polynomial chaos expansion method to assess probabilistic total transfer capability for power systems with renewables,” IEEE Transactions on Power Systems , vol. 36 , no. 3 , pp. 2573 - 2583 , May 2021.

A. Antoniadis, S. Lambert-Lacroix, and J. Poggi, “Random forests for global sensitivity analysis: a selective review,” Reliability Engineering & System Safety , vol. 206 , p. 107312 , Feb. 2021 .

C. Rasmussen and C. Williams, “ Gaussian processes for machine learning ,” in Adaptive Computation and Machine Learning . Cambridge: MIT Press, 2008.

B. Wirthl, S. Brandstaeter, J. Nitzler et al. , “Global sensitivity analysis based on Gaussian-process metamodelling for complex biomechanical problems,” International Journal for Numerical Methods in Biomedical Engineering , vol. 39 , no. 3 , p. e3675, Mar. 2023 .

W. Wei, L. Wu, J. Wang et al. , “Network equilibrium of coupled transportation and power distribution systems,” IEEE Transactions on Smart Grid , vol. 9 , no. 6 , pp. 6764 - 6779 , Nov. 2018 .

H. Mi, S. Chen, J. Ping et al. , “Traffic equilibrium considering heterogeneity across electric vehicles,” IEEE Transactions on Intelligent Transportation Systems , vol. 24 , no. 12 , pp. 14944 - 14956 , Dec. 2023 .

Y. Liu, Y. Wang, Y. Li et al. , “Multi-agent based optimal scheduling and trading for multi-microgrids integrated with urban transportation networks,” IEEE Transactions on Power Systems , vol. 36 , no. 3 , pp. 2197 - 2210 , May 2021.

I. Sobol’, “G lobal sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates,” Mathematics and Computers in Simulation , vol. 55 , no. 1 , pp. 271 - 280 , Feb. 2001 .

E. Schulz, M. Speekenbrink, and A. Krause, “A tutorial on Gaussian process regression: modelling, exploring, and exploiting functions,” Journal of Mathematical Psychology , vol. 85 , pp. 1 - 16 , Aug. 2018 .

S. Kucherenko, S. Tarantola, and P. Annoni, “Estimation of global sensitivity indices for models with dependent variables,” Computer Physics Communications , vol. 183 , no. 4 , pp. 937 - 946 , Apr. 2012 .

E. Beale and J. Forrest, “Global optimization using special ordered sets,” Mathematical Programming , vol. 10 , no. 1 , pp. 52 - 69 , Dec. 1976 .

S. Lv, S. Chen, Z. Wei et al. , “Power-transportation coordination: toward a hybrid economic-emission dispatch model,” IEEE Transactions on Power Systems , vol. 37 , no. 5 , pp. 3969 - 3981 , Sept. 2022.

H. Qin, H. Yang, H. Li et al ., “Highlights of key advances in China’s wind turbines technology in 2024,” Engineering Energy , vol. 19 , no. 1 , pp. 18 - 27 , Feb. 2025 .

C. Pandey, M. Wu, A. Oyeniran et al ., “Numerical study of a parabolic-trough CPV-T collector with spectral-splitting liquid filters,” Engineering Energy , vol. 19 , no. 6 , pp. 949 - 968 , Dec. 2025 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

Decentralized Energy Management of Power- and Hydrogen-based Microgrids in Wholesale Electricity Market as Price-maker

Multi-temporal Optimization of Virtual Power Plant in Energy-frequency Regulation Market Under Uncertainties

Robust Stability Analysis and Design of Parallel Grid-forming Converters in Islanded Microgrid

Enhanced Bi-layer Iterative Stochastic Robust Planning Method for Shared Rental Energy Storage in Industrial Microgrids

Optimal Scheduling of Data Center Virtual Power Plant in Electricity-Carbon Joint Market Under Uncertainty