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A methodology for optimal placement of energy hubs with electric vehicle charging stations and renewable generation

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  • Garau, Michele
  • Torsæter, Bendik Nybakk

Abstract

The use of electric vehicles and renewable energy sources can significantly contribute to the reduction of pollution levels, fostering a cleaner and more sustainable environment. In addition to their positive environmental impact, electric vehicles can also serve as energy storage units, enabling a bidirectional energy flow between the vehicles and the grid. Despite these promising prospects, a disjointed approach to charging infrastructure planning overlooks the synergies between the energy and transportation ecosystem. This calls for a holistic and coordinated approach to infrastructure development that harnesses the benefits emerging from the convergence of electric vehicles, renewable energy, and transport planning. This paper presents a methodology for the optimal placement of future Energy Hubs for electric vehicle charging and renewable generation. The methodology uses data from open-source datasets involving renewable energy sources, traffic density, charging patterns, road topology, and land use. The optimization problem is formulated as a multi-objective linear programming problem, with the objectives of minimizing the number of Energy Hub units, minimizing electric vehicles charging radius coverage and distance from power substations, and maximizing energy generation. The methodology is demonstrated through an application in Trondheim, Norway, which produces a Pareto front for decision-makers to evaluate the best trade-offs between objectives.

Suggested Citation

  • Garau, Michele & Torsæter, Bendik Nybakk, 2024. "A methodology for optimal placement of energy hubs with electric vehicle charging stations and renewable generation," Energy, Elsevier, vol. 304(C).
    • Handle: RePEc:eee:energy:v:304:y:2024:i:c:s0360544224018425
    DOI: 10.1016/j.energy.2024.132068
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    References listed on IDEAS

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    1. 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).
    2. Li, Chengzhe & Zhang, Libo & Ou, Zihan & Wang, Qunwei & Zhou, Dequn & Ma, Jiayu, 2022. "Robust model of electric vehicle charging station location considering renewable energy and storage equipment," Energy, Elsevier, vol. 238(PA).
    3. Xu Ouyang & Min Xu & Bojian Zhou, 2022. "An Elastic Demand Model for Locating Electric Vehicle Charging Stations," Networks and Spatial Economics, Springer, vol. 22(1), pages 1-31, March.
    4. Ayele, Getnet Tadesse & Mabrouk, Mohamed Tahar & Haurant, Pierrick & Laumert, Björn & Lacarrière, Bruno, 2019. "Optimal placement and sizing of heat pumps and heat only boilers in a coupled electricity and heating networks," Energy, Elsevier, vol. 182(C), pages 122-134.
    5. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    6. Yvenn Amara-Ouali & Yannig Goude & Pascal Massart & Jean-Michel Poggi & Hui Yan, 2021. "A Review of Electric Vehicle Load Open Data and Models," Energies, MDPI, vol. 14(8), pages 1-35, April.
    7. Dini, Anoosh & Hassankashi, Alireza & Pirouzi, Sasan & Lehtonen, Matti & Arandian, Behdad & Baziar, Ali Asghar, 2022. "A flexible-reliable operation optimization model of the networked energy hubs with distributed generations, energy storage systems and demand response," Energy, Elsevier, vol. 239(PA).
    8. Kong, Weiwei & Luo, Yugong & Feng, Guixuan & Li, Keqiang & Peng, Huei, 2019. "Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid," Energy, Elsevier, vol. 186(C).
    9. Alberto Danese & Michele Garau & Andreas Sumper & Bendik Nybakk Torsæter, 2021. "Electrical Infrastructure Design Methodology of Dynamic and Static Charging for Heavy and Light Duty Electric Vehicles," Energies, MDPI, vol. 14(12), pages 1-15, June.
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