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Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm

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  • Milad Akbari

    (Politecnico di Milano, Department of Energy, Via La Masa, 34, 20156 Milano (MI), Italy)

  • Morris Brenna

    (Politecnico di Milano, Department of Energy, Via La Masa, 34, 20156 Milano (MI), Italy)

  • Michela Longo

    (Politecnico di Milano, Department of Energy, Via La Masa, 34, 20156 Milano (MI), Italy)

Abstract

The advent of alternative vehicle technologies such as Electrical Vehicles (EVs) is an efficient effort to reduce the emission of carbon oxides and nitrogen oxides. Ironically, EVs poses concerns related to vehicle recharging and management. Due to the significance of charging station infrastructure, electric vehicles’ charging stations deployment is investigated in this work. Its aim is to consider several limitations such as the power of charging station, the average time needed for each recharge, and traveling distance per day. Initially, a mathematical formulation of the problem is framed. Then, this problem is optimized by application of Genetic Algorithm (GA), with the objective to calculate the necessary number of charging stations then finding the best positions to locate them to satisfy the clients demand.

Suggested Citation

  • Milad Akbari & Morris Brenna & Michela Longo, 2018. "Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1076-:d:139580
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    References listed on IDEAS

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    Cited by:

    1. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.
    2. 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.
    3. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries," Energies, MDPI, vol. 13(16), pages 1-20, August.
    4. 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.
    5. Xiangyu Luo & Rui Qiu, 2020. "Electric Vehicle Charging Station Location towards Sustainable Cities," IJERPH, MDPI, vol. 17(8), pages 1-22, April.
    6. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    7. Gang Xiao & Qihong Chen & Peng Xiao & Liyan Zhang & Quansen Rong, 2022. "Multiobjective Optimization for a Li-Ion Battery and Supercapacitor Hybrid Energy Storage Electric Vehicle," Energies, MDPI, vol. 15(8), pages 1-13, April.
    8. Yuping Zeng & Yang Cai & Guiyue Kou & Wei Gao & Datong Qin, 2018. "Energy Management for Plug-In Hybrid Electric Vehicle Based on Adaptive Simplified-ECMS," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    9. Mario Porru & Alessandro Serpi & Mario Mureddu & Alfonso Damiano, 2020. "A Multistage Design Procedure for Planning and Implementing Public Charging Infrastructures for Electric Vehicles," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
    10. Li Zhang & Ke Gong & Maozeng Xu, 2019. "Congestion Control in Charging Stations Allocation with Q-Learning," Sustainability, MDPI, vol. 11(14), pages 1-11, July.
    11. Mohd Bilal & Ibrahim Alsaidan & Muhannad Alaraj & Fahad M. Almasoudi & Mohammad Rizwan, 2022. "Techno-Economic and Environmental Analysis of Grid-Connected Electric Vehicle Charging Station Using AI-Based Algorithm," Mathematics, MDPI, vol. 10(6), pages 1-40, March.
    12. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    13. Mikołaj Schmidt & Paweł Zmuda-Trzebiatowski & Marcin Kiciński & Piotr Sawicki & Konrad Lasak, 2021. "Multiple-Criteria-Based Electric Vehicle Charging Infrastructure Design Problem," Energies, MDPI, vol. 14(11), pages 1-34, May.

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