IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v281y2023ics036054422301678x.html
   My bibliography  Save this article

Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning

Author

Listed:
  • Li, Yanbin
  • Wang, Jiani
  • Wang, Weiye
  • Liu, Chang
  • Li, Yun

Abstract

To accommodate the increased demand for electric vehicle(EV) charging in China, this paper examines electric vehicle charging station(EVCS) location strategies from the perspective of private investors, taking full account of the competitive environment of existing EVCSs in the region. First of all, a three-level location model considering dynamic pricing is developed, which includes user decisions, EVCS pricing, and EVCS location decisions. Then, the soft actor-critic(SAC) reinforcement learning algorithm is used to train the optimal pricing strategy for EVCS to guarantee the maximum cumulative revenue. The proposed methodology is verified through case studies based on an industrial park in China. The results show that the proposed methodology can make more economical and scientific location decisions than the traditional method. The dynamic pricing method based on reinforcement learning can provide a reference for the location and operation of more EVCSs.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:281:y:2023:i:c:s036054422301678x
    DOI: 10.1016/j.energy.2023.128284
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422301678X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128284?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ying, Zhou & Xin-gang, Zhao, 2021. "The impact of Renewable Portfolio Standards on carbon emission trading under the background of China’s electricity marketization reform," Energy, Elsevier, vol. 226(C).
    2. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    3. Michael L. Littman, 2015. "Reinforcement learning improves behaviour from evaluative feedback," Nature, Nature, vol. 521(7553), pages 445-451, May.
    4. 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).
    5. Liu, Yuechen Sophia & Tayarani, Mohammad & Gao, H. Oliver, 2022. "An activity-based travel and charging behavior model for simulating battery electric vehicle charging demand," Energy, Elsevier, vol. 258(C).
    6. 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).
    7. Hu, Zechun & Zhan, Kaiqiao & Zhang, Hongcai & Song, Yonghua, 2016. "Pricing mechanisms design for guiding electric vehicle charging to fill load valley," Applied Energy, Elsevier, vol. 178(C), pages 155-163.
    8. Tegnér, Martin & Ernstsen, Rune Ramsdal & Skajaa, Anders & Poulsen, Rolf, 2017. "Risk-minimisation in electricity markets: Fixed price, unknown consumption," Energy Economics, Elsevier, vol. 68(C), pages 423-439.
    9. Weicheng Hou & Qingsong Luo & Xiangdong Wu & Yimin Zhou & Gangquan Si & Ramon Costa-Castelló, 2021. "Multiobjective Optimization of Large-Scale EVs Charging Path Planning and Charging Pricing Strategy for Charging Station," Complexity, Hindawi, vol. 2021, pages 1-17, February.
    10. Xingping Zhang & Yanni Liang & Yakun Zhang & Yinhe Bu & Hongyang Zhang, 2017. "Charge Pricing Optimization Model for Private Charging Piles in Beijing," Sustainability, MDPI, vol. 9(11), pages 1-15, November.
    11. Ren, Xianqiang & Zhang, Huiming & Hu, Ruohan & Qiu, Yueming, 2019. "Location of electric vehicle charging stations: A perspective using the grey decision-making model," Energy, Elsevier, vol. 173(C), pages 548-553.
    12. Yang, Zaoli & Li, Qin & Yan, Yamin & Shang, Wen-Long & Ochieng, Washington, 2022. "Examining influence factors of Chinese electric vehicle market demand based on online reviews under moderating effect of subsidy policy," Applied Energy, Elsevier, vol. 326(C).
    13. Li, Na & Jiang, Yue & Zhang, Zhi-Hai, 2021. "A two-stage ambiguous stochastic program for electric vehicle charging station location problem with valet charging service," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 149-171.
    14. Jia Liu & Jin Huang & Jinzhi Hu, 2022. "Multi-objective optimisation method of electric vehicle charging station based on non-dominated sorting genetic algorithm," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 44(5/6), pages 413-426.
    15. 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).
    16. Zhang, Xingping & Liang, Yanni & Liu, Wenfeng, 2017. "Pricing model for the charging of electric vehicles based on system dynamics in Beijing," Energy, Elsevier, vol. 119(C), pages 218-234.
    17. Liu, Zhiqing & Geng, Yong & Dai, Hancheng & Wilson, Jeffrey & Xie, Yang & Wu, Rui & You, Wei & Yu, Zhongjue, 2018. "Regional impacts of launching national carbon emissions trading market: A case study of Shanghai," Applied Energy, Elsevier, vol. 230(C), pages 232-240.
    18. Lixing Chen & Zhong Chen & Xueliang Huang & Long Jin, 2016. "A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways," Energies, MDPI, vol. 9(5), pages 1-18, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hamza El Hafdaoui & Hamza El Alaoui & Salma Mahidat & Zakaria El Harmouzi & Ahmed Khallaayoun, 2023. "Impact of Hot Arid Climate on Optimal Placement of Electric Vehicle Charging Stations," Energies, MDPI, vol. 16(2), pages 1-19, January.
    2. Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Haider Ali & Inam Bari & Ben Horan & Saad Mekhilef & Muhammad Asif & Saeed Ahmed & Anzar Mahmood, 2020. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network," Sustainability, MDPI, vol. 12(23), pages 1-28, December.
    3. Sami M. Alshareef & Ahmed Fathy, 2023. "Efficient Red Kite Optimization Algorithm for Integrating the Renewable Sources and Electric Vehicle Fast Charging Stations in Radial Distribution Networks," Mathematics, MDPI, vol. 11(15), pages 1-30, July.
    4. 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).
    5. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    6. Verónica Anadón Martínez & Andreas Sumper, 2023. "Planning and Operation Objectives of Public Electric Vehicle Charging Infrastructures: A Review," Energies, MDPI, vol. 16(14), pages 1-41, July.
    7. 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).
    8. Ferro, G. & Minciardi, R. & Robba, M., 2020. "A user equilibrium model for electric vehicles: Joint traffic and energy demand assignment," Energy, Elsevier, vol. 198(C).
    9. Xingping Zhang & Yanni Liang & Yakun Zhang & Yinhe Bu & Hongyang Zhang, 2017. "Charge Pricing Optimization Model for Private Charging Piles in Beijing," Sustainability, MDPI, vol. 9(11), pages 1-15, November.
    10. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    11. 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.
    12. Loni, Abdolah & Asadi, Somayeh, 2023. "Data-driven equitable placement for electric vehicle charging stations: Case study San Francisco," Energy, Elsevier, vol. 282(C).
    13. Liang, Yanni & Zhang, Xingping, 2018. "Battery swap pricing and charging strategy for electric taxis in China," Energy, Elsevier, vol. 147(C), pages 561-577.
    14. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    15. 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).
    16. Su Su & Hao Li & David Wenzhong Gao, 2017. "Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits," Energies, MDPI, vol. 10(7), pages 1-15, July.
    17. Deveci, Muhammet & Erdogan, Nuh & Pamucar, Dragan & Kucuksari, Sadik & Cali, Umit, 2023. "A rough Dombi Bonferroni based approach for public charging station type selection," Applied Energy, Elsevier, vol. 345(C).
    18. Song, Yanqiu & Shangguan, Lingzhi & Li, Guijun, 2021. "Simulation analysis of flexible concession period contracts in electric vehicle charging infrastructure public-private-partnership (EVCI-PPP) projects based on time-of-use (TOU) charging price strateg," Energy, Elsevier, vol. 228(C).
    19. Di Xu & Wenhui Pei & Qi Zhang, 2022. "Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience," Energies, MDPI, vol. 15(14), pages 1-16, July.
    20. Qi, Wei & Shen, Bo & Zhang, Hongcai & Shen, Zuo-Jun Max, 2017. "Sharing demand-side energy resources - A conceptual design," Energy, Elsevier, vol. 135(C), pages 455-465.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:281:y:2023:i:c:s036054422301678x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.