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Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)

Author

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  • Guozhong Liu

    (School of Electrical Engineering & Intelligentization, Dongguan University of technology, Dongguan 523808, China)

  • Li Kang

    (School of Electrical Engineering & Intelligentization, Dongguan University of technology, Dongguan 523808, China)

  • Zeyu Luan

    (School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia)

  • Jing Qiu

    (School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia)

  • Fenglei Zheng

    (Dongguan Power Supply Bureau, Dongguan 523808, China)

Abstract

The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.

Suggested Citation

  • Guozhong Liu & Li Kang & Zeyu Luan & Jing Qiu & Fenglei Zheng, 2019. "Charging Station and Power Network Planning for Integrated Electric Vehicles (EVs)," Energies, MDPI, vol. 12(13), pages 1-22, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2595-:d:246000
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    References listed on IDEAS

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    Cited by:

    1. Ruifeng Shi & Jiahua Liu & Zhenhong Liao & Li Niu & Eke Ibrahim & Fang Fu, 2019. "An Electric Taxi Charging Station Planning Scheme Based on an Improved Destination Choice Method," Energies, MDPI, vol. 12(19), pages 1-21, October.
    2. Wang, Ning & Tian, Hangqi & Wu, Huahua & Liu, Qiaoqian & Luan, Jie & Li, Yuan, 2023. "Cost-oriented optimization of the location and capacity of charging stations for the electric Robotaxi fleet," Energy, Elsevier, vol. 263(PC).
    3. Miguel Campaña & Esteban Inga & Jorge Cárdenas, 2021. "Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities," Energies, MDPI, vol. 14(16), pages 1-16, August.
    4. Hipolito, F. & Vandet, C.A. & Rich, J., 2022. "Charging, steady-state SoC and energy storage distributions for EV fleets," Applied Energy, Elsevier, vol. 317(C).
    5. Bong-Gi Choi & Byeong-Chan Oh & Sungyun Choi & Sung-Yul Kim, 2020. "Selecting Locations of Electric Vehicle Charging Stations Based on the Traffic Load Eliminating Method," Energies, MDPI, vol. 13(7), pages 1-20, April.
    6. Andrea Stabile & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "An Algorithm for Optimization of Recharging Stops: A Case Study of Electric Vehicle Charging Stations on Canadian’s Ontario Highway 401," Energies, MDPI, vol. 13(8), pages 1-19, April.
    7. Leon Fidele Nishimwe H. & Sung-Guk Yoon, 2021. "Combined Optimal Planning and Operation of a Fast EV-Charging Station Integrated with Solar PV and ESS," Energies, MDPI, vol. 14(11), pages 1-18, May.
    8. Shafqat Jawad & Junyong Liu, 2023. "Electrical Vehicle Charging Load Mobility Analysis Based on a Spatial–Temporal Method in Urban Electrified-Transportation Networks," Energies, MDPI, vol. 16(13), pages 1-14, July.
    9. Akhtar Hussain & Van-Hai Bui & Ju-Won Baek & Hak-Man Kim, 2019. "Stationary Energy Storage System for Fast EV Charging Stations: Simultaneous Sizing of Battery and Converter," Energies, MDPI, vol. 12(23), pages 1-17, November.
    10. Sheik Mohammed S. & Femin Titus & Sudhakar Babu Thanikanti & Sulaiman S. M. & Sanchari Deb & Nallapaneni Manoj Kumar, 2022. "Charge Scheduling Optimization of Plug-In Electric Vehicle in a PV Powered Grid-Connected Charging Station Based on Day-Ahead Solar Energy Forecasting in Australia," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    11. Mihai Rata & Gabriela Rata & Constantin Filote & Maria Simona Raboaca & Adrian Graur & Ciprian Afanasov & Andreea-Raluca Felseghi, 2019. "The ElectricalVehicle Simulator for Charging Station in Mode 3 of IEC 61851-1 Standard," Energies, MDPI, vol. 13(1), pages 1-10, December.
    12. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    13. Vitalii Naumov, 2021. "Substantiation of Loading Hub Location for Electric Cargo Bikes Servicing City Areas with Restricted Traffic," Energies, MDPI, vol. 14(4), pages 1-16, February.
    14. Seyfettin Vadi & Ramazan Bayindir & Alperen Mustafa Colak & Eklas Hossain, 2019. "A Review on Communication Standards and Charging Topologies of V2G and V2H Operation Strategies," Energies, MDPI, vol. 12(19), pages 1-27, September.
    15. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    16. Zeinab Teimoori & Abdulsalam Yassine, 2022. "A Review on Intelligent Energy Management Systems for Future Electric Vehicle Transportation," Sustainability, MDPI, vol. 14(21), pages 1-23, October.

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