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Robust model of electric vehicle charging station location considering renewable energy and storage equipment

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  • Li, Chengzhe
  • Zhang, Libo
  • Ou, Zihan
  • Wang, Qunwei
  • Zhou, Dequn
  • Ma, Jiayu

Abstract

The location of electric vehicle charging station (EVCS) is one of the critical problems that restricts the popularization of electric vehicle (EV), and the combination of EVCS and distributed renewable energy can stabilize the fluctuation of renewable energy output. This article takes a micro-grid composed of the power distribution such as wind power and photovoltaic (PV), EVCSs and energy storage systems (ESS) as the research object. The uncertainties of EVs’ charging demand and distributed renewable energy output are considered. A robust optimization model for the location of charging stations with distributed energy is proposed based on the combination of the road network and the grid. Load fluctuation rate is used to evaluate the degree of fit between the renewable energy uncertain output curve and the charging demand curve to determine the appropriate capacity of the wind and PV generation system and ESS. The method of kernel density estimation is used to improve the issue of over-conservatism of the robust optimization. Finally, a simulation is carried out on a network which consists of an IEEE 33-node power distribution network and a 25-node transportation system. The robustness and economy of the model are demonstrated by the results of simulation given.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:238:y:2022:i:pa:s0360544221019617
    DOI: 10.1016/j.energy.2021.121713
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    References listed on IDEAS

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    3. 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).
    4. Nagaraju Dharavat & Suresh Kumar Sudabattula & Suresh Velamuri & Sachin Mishra & Naveen Kumar Sharma & Mohit Bajaj & Elmazeg Elgamli & Mokhtar Shouran & Salah Kamel, 2022. "Optimal Allocation of Renewable Distributed Generators and Electric Vehicles in a Distribution System Using the Political Optimization Algorithm," Energies, MDPI, vol. 15(18), pages 1-25, September.
    5. Xian Huang & Wentong Ji & Xiaorong Ye & Zhangjie Feng, 2023. "Configuration Planning of Expressway Self-Consistent Energy System Based on Multi-Objective Chance-Constrained Programming," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    6. Clairand, Jean-Michel & González-Rodríguez, Mario & Kumar, Rajesh & Vyas, Shashank & Escrivá-Escrivá, Guillermo, 2022. "Optimal siting and sizing of electric taxi charging stations considering transportation and power system requirements," Energy, Elsevier, vol. 256(C).
    7. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    8. Young-Eun Jeon & Suk-Bok Kang & Jung-In Seo, 2022. "Hybrid Predictive Modeling for Charging Demand Prediction of Electric Vehicles," Sustainability, MDPI, vol. 14(9), pages 1-15, April.
    9. 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).
    10. Shi, Lei & Wu, Rongxin & Lin, Boqiang, 2023. "Where will go for electric vehicles in China after the government subsidy incentives are abolished? A controversial consumer perspective," Energy, Elsevier, vol. 262(PA).
    11. Lai, Chun Sing & Chen, Dashen & Zhang, Jinning & Zhang, Xin & Xu, Xu & Taylor, Gareth A. & Lai, Loi Lei, 2022. "Profit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networks," Energy, Elsevier, vol. 259(C).
    12. Luo, Jianing & Yuan, Yanping & Joybari, Mahmood Mastani & Cao, Xiaoling, 2024. "Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems," Renewable Energy, Elsevier, vol. 224(C).
    13. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).
    14. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).

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