IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6151-d1223953.html
   My bibliography  Save this article

Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation

Author

Listed:
  • Heping Jia

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Qianxin Ma

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yun Li

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Mingguang Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Dunnan Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

Fossil energy consumption and environmental protection issues have pushed electric vehicles (EVs) to become one of the alternatives to traditional fossil-fuel vehicles. EV refers to a vehicle that uses electric energy as power and is driven by an electric motor. The electric energy of EVs is stored in batteries. When the EV is not traveling, the battery can provide power for other loads. Therefore, with the increase in the number of EVs and the load of the power grid, the EV-to-grid (V2G) mode, which uses EVs to supply power to the power grid, has gradually entered the field of vision of researchers. The physical connection mode, charge and discharge technology, and energy management strategy are the main topics of the current review papers; however, there is a lack of systematic research on V2G modeling, framework, and business models. This paper describes the concepts of the spatio-temporal distribution model and the adjustable capacity of EVs. In addition, common constraints and methods in optimization are introduced. Moreover, this paper introduces the interactive relationship among power grids, load aggregators, and EV users. Furthermore, the business model of V2G is introduced and analyzed from various perspectives. Finally, the future development of V2G is pointed out. This paper’s goal is to provide an overview of the present V2G application scenarios and to identify any challenges that must be overcome.

Suggested Citation

  • Heping Jia & Qianxin Ma & Yun Li & Mingguang Liu & Dunnan Liu, 2023. "Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation," Energies, MDPI, vol. 16(17), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6151-:d:1223953
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6151/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6151/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hou, Zhuoran & Guo, Jianhua & Li, Jihao & Hu, Jinchen & Sun, Wen & Zhang, Yuanjian, 2023. "Exploration the pathways of connected electric vehicle design: A vehicle-environment cooperation energy management strategy," Energy, Elsevier, vol. 271(C).
    2. Yao, Zhaosheng & Wang, Zhiyuan & Ran, Lun, 2023. "Smart charging and discharging of electric vehicles based on multi-objective robust optimization in smart cities," Applied Energy, Elsevier, vol. 343(C).
    3. 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).
    4. Sulaiman, Mohd Herwan & Mustaffa, Zuriani & Zakaria, Nor Farizan & Saari, Mohd Mawardi, 2023. "Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle," Energy, Elsevier, vol. 279(C).
    5. Awab Baqar & Mamadou Baïlo Camara & Brayima Dakyo, 2023. "Supercapacitors Fast Ageing Control in Residential Microgrid Based Photovoltaic/Fuel Cell/Electric Vehicle Charging Station," Energies, MDPI, vol. 16(13), pages 1-25, June.
    6. Mousavizade, Mirsaeed & Bai, Feifei & Garmabdari, Rasoul & Sanjari, Mohammad & Taghizadeh, Foad & Mahmoudian, Ali & Lu, Junwei, 2023. "Adaptive control of V2Gs in islanded microgrids incorporating EV owner expectations," Applied Energy, Elsevier, vol. 341(C).
    7. Xin-gang, Zhao & Ling-zhi, Ren & Yu-zhuo, Zhang & Guan, Wan, 2018. "Evolutionary game analysis on the behavior strategies of power producers in renewable portfolio standard," Energy, Elsevier, vol. 162(C), pages 505-516.
    8. Sharma, S. & Jain, Prerna, 2023. "Risk-averse integrated DR and dynamic V2G scheduling of parking lot operator for enhanced market efficiency," Energy, Elsevier, vol. 275(C).
    9. Philip, Thara & Whitehead, Jake & Prato, Carlo G., 2023. "Adoption of electric vehicles in a laggard, car-dependent nation: Investigating the potential influence of V2G and broader energy benefits on adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    10. Abubakr, Hussein & Lashab, Abderezak & Vasquez, Juan C. & Mohamed, Tarek Hassan & Guerrero, Josep M., 2023. "Novel V2G regulation scheme using Dual-PSS for PV islanded microgrid," Applied Energy, Elsevier, vol. 340(C).
    11. Li, Yipu & Su, Hao & Zhou, Yun & Chen, Lixia & Shi, Yiwei & Li, Hengjie & Feng, Donghan, 2023. "Two-stage real-time optimal electricity dispatch strategy for urban residential quarter with electric vehicles’ charging load," Energy, Elsevier, vol. 268(C).
    12. Singh, Bharat & Kumar, Ashwani, 2023. "Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program," Energy, Elsevier, vol. 278(PA).
    13. Liu, Shuohan & Cao, Yue & Ni, Qiang & Xu, Lexi & Zhu, Yongdong & Zhang, Xin, 2023. "Towards reservation-based E-mobility service via hybrid of V2V and G2V charging modes," Energy, Elsevier, vol. 268(C).
    14. de la Torre, S. & Aguado, J.A. & Sauma, E., 2023. "Optimal scheduling of ancillary services provided by an electric vehicle aggregator," Energy, Elsevier, vol. 265(C).
    15. Bouallaga, Anouar & Davigny, Arnaud & Courtecuisse, Vincent & Robyns, Benoit, 2017. "Methodology for technical and economic assessment of electric vehicles integration in distribution grid," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 172-189.
    16. Wu, Ji & Su, Hao & Meng, Jinhao & Lin, Mingqiang, 2023. "Electric vehicle charging scheduling considering infrastructure constraints," Energy, Elsevier, vol. 278(PA).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Weiqi Pan & Xiaorong Yu & Zishan Guo & Tao Qian & Yang Li, 2024. "Online EVs Vehicle-to-Grid Scheduling Coordinated with Multi-Energy Microgrids: A Deep Reinforcement Learning-Based Approach," Energies, MDPI, vol. 17(11), pages 1-20, May.

    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. Qingyuan Yan & Yang Gao & Ling Xing & Binrui Xu & Yanxue Li & Weili Chen, 2024. "Optimal Scheduling for Increased Satisfaction of Both Electric Vehicle Users and Grid Fast-Charging Stations by SOR&KANO and MVO in PV-Connected Distribution Network," Energies, MDPI, vol. 17(14), pages 1-36, July.
    2. Zhang, Rui & Yu, Jilai, 2024. "Evaluating multi-dimensional response capability of electric bus considering carbon emissions and traffic index," Energy, Elsevier, vol. 286(C).
    3. Wu, Jiabin & Li, Qihang & Bie, Yiming & Zhou, Wei, 2024. "Location-routing optimization problem for electric vehicle charging stations in an uncertain transportation network: An adaptive co-evolutionary clustering algorithm," Energy, Elsevier, vol. 304(C).
    4. Li, Jingjing & Wang, Zhaoxin & Li, Hui & Jiao, Jianling, 2024. "Which policy can effectively promote the formal recycling of power batteries in China?," Energy, Elsevier, vol. 299(C).
    5. Jiang, Hou & Yao, Ling & Lu, Ning & Qin, Jun & Zhang, Xiaotong & Liu, Tang & Zhang, Xingxing & Zhou, Chenghu, 2024. "Exploring the optimization of rooftop photovoltaic scale and spatial layout under curtailment constraints," Energy, Elsevier, vol. 293(C).
    6. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
    7. Huachun Han & Huiyu Miu & Shukang Lv & Xiaodong Yuan & Yi Pan & Fei Zeng, 2024. "Fast Charging Guidance and Pricing Strategy Considering Different Types of Electric Vehicle Users’ Willingness to Charge," Energies, MDPI, vol. 17(18), pages 1-21, September.
    8. Wang, Qi & Huang, Chunyi & Wang, Chengmin & Li, Kangping & Xie, Ning, 2024. "Joint optimization of bidding and pricing strategy for electric vehicle aggregator considering multi-agent interactions," Applied Energy, Elsevier, vol. 360(C).
    9. Zeng, Lijun & Du, Wenjing & Zhang, Wencheng & Zhao, Laijun & Wang, Zhaohua, 2023. "An inter-provincial cooperation model under Renewable Portfolio Standard policy," Energy, Elsevier, vol. 269(C).
    10. Zhang, Tianren & Huang, Yuping & Liao, Hui & Liang, Yu, 2023. "A hybrid electric vehicle load classification and forecasting approach based on GBDT algorithm and temporal convolutional network," Applied Energy, Elsevier, vol. 351(C).
    11. Secinaro, Silvana & Calandra, Davide & Lanzalonga, Federico & Ferraris, Alberto, 2022. "Electric vehicles’ consumer behaviours: Mapping the field and providing a research agenda," Journal of Business Research, Elsevier, vol. 150(C), pages 399-416.
    12. K. A. Indu Sailaja & K. Rahimunnisa, 2024. "Analysis of energy management in a hybrid renewable power system using MOA technique," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 18989-19011, July.
    13. 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).
    14. Jamali, Mohammad-Bagher & Rasti-Barzoki, Morteza & Khosroshahi, Hossein & Altmann, Jörn, 2022. "An evolutionary game-theoretic approach to study the technological transformation of the industrial sector toward renewable electricity procurement: A case study of Iran," Applied Energy, Elsevier, vol. 318(C).
    15. Despoina Kothona & Aggelos S. Bouhouras, 2022. "A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks," Energies, MDPI, vol. 15(10), pages 1-17, May.
    16. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Masahiro Furukakoi & Paras Mandal & Tomonobu Senjyu, 2023. "Integrated Multi-Criteria Planning for Resilient Renewable Energy-Based Microgrid Considering Advanced Demand Response and Uncertainty," Energies, MDPI, vol. 16(19), pages 1-25, September.
    17. Xiangchu Xu & Zewei Zhan & Zengqiang Mi & Ling Ji, 2023. "An Optimized Decision Model for Electric Vehicle Aggregator Participation in the Electricity Market Based on the Stackelberg Game," Sustainability, MDPI, vol. 15(20), pages 1-26, October.
    18. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
    19. Sagar Hossain & Md. Rokonuzzaman & Kazi Sajedur Rahman & A. K. M. Ahasan Habib & Wen-Shan Tan & Md Mahmud & Shahariar Chowdhury & Sittiporn Channumsin, 2023. "Grid-Vehicle-Grid (G2V2G) Efficient Power Transmission: An Overview of Concept, Operations, Benefits, Concerns, and Future Challenges," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    20. Ouyang, Xu & Xu, Min, 2022. "Promoting green transportation under the belt and Road Initiative: Locating charging stations considering electric vehicle users’ travel behavior," Transport Policy, Elsevier, vol. 116(C), pages 58-80.

    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:gam:jeners:v:16:y:2023:i:17:p:6151-:d:1223953. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.