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author:

Jiang, Changxu (Jiang, Changxu.) [1] | Lu, Yuejun (Lu, Yuejun.) [2] | Yuan, Yujuan (Yuan, Yujuan.) [3] | Zhuang, Pengwei (Zhuang, Pengwei.) [4] | Xu, Hao (Xu, Hao.) [5] | Lin, Junjie (Lin, Junjie.) [6] | Shao, Zhenguo (Shao, Zhenguo.) [7]

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EI

Abstract:

To improve users' satisfaction during intercity travel and promote the development of the 'high-speed + photovoltaic' new model, it is necessary to make reasonable planning for the location of charging facilities, photovoltaics, and energy storage on the highway. Firstly, a mileage anxiety model is constructed based on user heterogeneity to describe the charging psychological characteristics of different types of users more accurately. Secondly, a multi-objective planning model is built, considering the sum of construction, operation, and expansion costs of charging facilities and power equipment, as well as the comprehensive user charging costs, which include the cost of electric vehicle charging time, charging waiting time, and charging range anxiety. Then, the fast non-dominated sorting multi-objective genetic algorithm and evidence reasoning decision-making method are adopted to solve the problem and obtain the optimal expansion planning scheme of charging facilities and distribution networks. Finally, the proposed model is simulated and verified with the actual traffic flow data of G15 Shenhai Expressway and the IEEE33 -bus as examples. The simulation results show that the reasonable location of charging facilities, photovoltaics, and energy storage can effectively reduce construction and operation costs and improve users' satisfaction with travel. © 2025 Power System Technology Press. All rights reserved.

Keyword:

Charging stations Charging time Costs Decision making Digital storage Electric power distribution Energy storage Expansion Facilities Genetic algorithms Highway planning Traffic control

Community:

  • [ 1 ] [Jiang, Changxu]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 2 ] [Jiang, Changxu]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 3 ] [Lu, Yuejun]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 4 ] [Lu, Yuejun]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 5 ] [Yuan, Yujuan]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 6 ] [Yuan, Yujuan]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 7 ] [Zhuang, Pengwei]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 8 ] [Zhuang, Pengwei]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 9 ] [Xu, Hao]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 10 ] [Xu, Hao]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 11 ] [Lin, Junjie]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 12 ] [Lin, Junjie]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China
  • [ 13 ] [Shao, Zhenguo]College of Electrical Engineering and Automation, Fuzhou University, Fujian Province, Fuzhou; 350108, China
  • [ 14 ] [Shao, Zhenguo]Fujian Smart Electrical Engineering Technology Research Center, Fujian Province, Fuzhou; 350108, China

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Source :

Power System Technology

ISSN: 1000-3673

Year: 2025

Issue: 9

Volume: 49

Page: 3881-3890

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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