IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1160-d328223.html
   My bibliography  Save this article

Charging and Discharging Scheduling for Electrical Vehicles Using a Shapley-Value Approach

Author

Listed:
  • Marija Zima-Bockarjova

    (ABB Corporate Research Center, 5405 Baden-Dättwil, Switzerland)

  • Antans Sauhats

    (Institute of Power Engineering, Riga Technical University (RTU), LV-1658 Riga, Latvia)

  • Lubov Petrichenko

    (Institute of Power Engineering, Riga Technical University (RTU), LV-1658 Riga, Latvia)

  • Roman Petrichenko

    (Institute of Power Engineering, Riga Technical University (RTU), LV-1658 Riga, Latvia)

Abstract

The number of electric vehicles (EV) in the world has been increasing and is gaining momentum. The large-scale use of EVs in public life has initiated the need to establish EV battery charging services within the power system. Currently, EVs serve as a transportation tool and also as a flexible load. This publication examines the possibility of the owner of an electric vehicle choosing a battery recharging point, as well as of the involvement of several decision makers in the selection of a charging schedule. This problem is important because we assume that a significant proportion of EVs mainly use two parking spaces, one located close to the place of residence and another close to the workplace. We accept and prove that a car charging station can be created by the employer (company) and implemented in the best interests of the employer and the employee (EV owner). For that, a coalition between the company and the EV owner has to be formed. To support rational decisions, this study solves the problem using the cooperative game theory and designs a payment distribution mechanism based on the Shapley value. The results obtained prove that the coalition is beneficial under different conditions, which depend on the capacity of the EV, the distance between the workplace and the place of residence, the difference in the electricity prices of the day, as well as the consumption of the company. In order to estimate the coalition’s gain, it is necessary to take into account the structure of the power tariff system for both the company and the EV owner. Furthermore, we prove that the presence of a coalition allows the company and the EV owner to reduce the annual fee for consumed power. The results of this analysis could be adopted by decision makers such as government agencies, companies, EV owners, and they are recommended for potential investors for the development of transport electrification and smart energy.

Suggested Citation

  • Marija Zima-Bockarjova & Antans Sauhats & Lubov Petrichenko & Roman Petrichenko, 2020. "Charging and Discharging Scheduling for Electrical Vehicles Using a Shapley-Value Approach," Energies, MDPI, vol. 13(5), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1160-:d:328223
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1160/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/5/1160/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitrios Rizopoulos & Domokos Esztergár-Kiss, 2020. "A Method for the Optimization of Daily Activity Chains Including Electric Vehicles," Energies, MDPI, vol. 13(4), pages 1-21, February.
    2. Madina, Carlos & Zamora, Inmaculada & Zabala, Eduardo, 2016. "Methodology for assessing electric vehicle charging infrastructure business models," Energy Policy, Elsevier, vol. 89(C), pages 284-293.
    3. Gerardo J. Osório & Miadreza Shafie-khah & Pedro D. L. Coimbra & Mohamed Lotfi & João P. S. Catalão, 2018. "Distribution System Operation with Electric Vehicle Charging Schedules and Renewable Energy Resources," Energies, MDPI, vol. 11(11), pages 1-20, November.
    4. Steffen Limmer, 2019. "Evaluation of Optimization-Based EV Charging Scheduling with Load Limit in a Realistic Scenario," Energies, MDPI, vol. 12(24), pages 1-16, December.
    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. Kouridis, Ch & Vlachokostas, Ch, 2022. "Towards decarbonizing road transport: Environmental and social benefit of vehicle fleet electrification in urban areas of Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    2. Héricles Eduardo Oliveira Farias & Camilo Alberto Sepulveda Rangel & Leonardo Weber Stringini & Luciane Neves Canha & Daniel Pegoraro Bertineti & Wagner da Silva Brignol & Zeno Iensen Nadal, 2021. "Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(5), pages 1-27, March.
    3. Tovar Rosas, Mario A. & Pérez, Miguel Robles & Martínez Pérez, E. Rafael, 2022. "Itineraries for charging and discharging a BESS using energy predictions based on a CNN-LSTM neural network model in BCS, Mexico," Renewable Energy, Elsevier, vol. 188(C), pages 1141-1165.
    4. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    5. Yan Bao & Fangyu Chang & Jinkai Shi & Pengcheng Yin & Weige Zhang & David Wenzhong Gao, 2022. "An Approach for Pricing of Charging Service Fees in an Electric Vehicle Public Charging Station Based on Prospect Theory," Energies, MDPI, vol. 15(14), pages 1-20, July.
    6. Zeinab Teimoori & Abdulsalam Yassine, 2022. "A Review on Intelligent Energy Management Systems for Future Electric Vehicle Transportation," Sustainability, MDPI, vol. 14(21), pages 1-23, October.

    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. Jairo Ortega & János Tóth & Tamás Péter & Sarbast Moslem, 2020. "An Integrated Model of Park-And-Ride Facilities for Sustainable Urban Mobility," Sustainability, MDPI, vol. 12(11), pages 1-15, June.
    2. Anne Christine Lusk & Xin Li & Qiming Liu, 2023. "If the Government Pays for Full Home-Charger Installation, Would Affordable-Housing and Middle-Income Residents Buy Electric Vehicles?," Sustainability, MDPI, vol. 15(5), pages 1-26, March.
    3. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    4. Konstantinos Kotsalos & Ismael Miranda & Nuno Silva & Helder Leite, 2019. "A Horizon Optimization Control Framework for the Coordinated Operation of Multiple Distributed Energy Resources in Low Voltage Distribution Networks," Energies, MDPI, vol. 12(6), pages 1-27, March.
    5. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    6. Jan Pekárek, 2017. "A Model of Charging Service Demand for the Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(5), pages 1741-1750.
    7. Se Hoon Baik & Young Gyu Jin & Yong Tae Yoon, 2018. "Determining Equipment Capacity of Electric Vehicle Charging Station Operator for Profit Maximization," Energies, MDPI, vol. 11(9), pages 1-15, September.
    8. Kim, Hyunjung & Kim, Dae-Wook & Kim, Man-Keun, 2022. "Economics of charging infrastructure for electric vehicles in Korea," Energy Policy, Elsevier, vol. 164(C).
    9. Yian Yan & Huang Wang & Jiuchun Jiang & Weige Zhang & Yan Bao & Mei Huang, 2019. "Research on Configuration Methods of Battery Energy Storage System for Pure Electric Bus Fast Charging Station," Energies, MDPI, vol. 12(3), pages 1-17, February.
    10. Ramadhani, Farah & Hussain, M.A. & Mokhlis, Hazlie & Fazly, Muhamad & Ali, Jarinah Mohd., 2019. "Evaluation of solid oxide fuel cell based polygeneration system in residential areas integrating with electric charging and hydrogen fueling stations for vehicles," Applied Energy, Elsevier, vol. 238(C), pages 1373-1388.
    11. Bassem Haidar & Pascal da Costa & Jan Lepoutre & Fabrice Vidal, 2020. "Which combination of battery capacity and charging power for battery electric vehicles: urban versus rural French case studies," Post-Print hal-03071656, HAL.
    12. Anamarija Falkoni & Antun Pfeifer & Goran Krajačić, 2020. "Vehicle-to-Grid in Standard and Fast Electric Vehicle Charging: Comparison of Renewable Energy Source Utilization and Charging Costs," Energies, MDPI, vol. 13(6), pages 1-22, March.
    13. Baek, Seungju & Lee, Sanguk & Shin, Myunghwan & Lee, Jongtae & Lee, Kihyung, 2022. "Analysis of combustion and exhaust characteristics according to changes in the propane content of LPG," Energy, Elsevier, vol. 239(PC).
    14. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    15. Schulz, Felix & Rode, Johannes, 2022. "Public charging infrastructure and electric vehicles in Norway," Energy Policy, Elsevier, vol. 160(C).
    16. Nian, Victor & Hari, M.P. & Yuan, Jun, 2019. "A new business model for encouraging the adoption of electric vehicles in the absence of policy support," Applied Energy, Elsevier, vol. 235(C), pages 1106-1117.
    17. Jairo Ortega & Sarbast Moslem & János Tóth & Tamás Péter & Juan Palaguachi & Mario Paguay, 2020. "Using Best Worst Method for Sustainable Park and Ride Facility Location," Sustainability, MDPI, vol. 12(23), pages 1-18, December.
    18. Wouter P. L. van Galen & Bob Walrave & Sharon A. M. Dolmans & A. Georges L. Romme, 2021. "Charging for Collaboration: Exploring the Dynamics of Temporal Fit in Interdependent Constellations for Innovation," Energies, MDPI, vol. 14(17), pages 1-23, August.
    19. Sutton, Katrina & Hardman, Scott & Tal, Gil, 2022. "Strategies to Reduce Congestion and Increase Access to Electric Vehicle Charging Stations at Workplaces," Institute of Transportation Studies, Working Paper Series qt2345r48k, Institute of Transportation Studies, UC Davis.
    20. Goldschmidt, Rüdiger & Richter, Andreas & Pfeil, Raphael, 2019. "Active stakeholder involvement and organisational tasks as factors for an effective communication and governance strategy in the promotion of e-taxis. Results from a field research lab," Energy Policy, Elsevier, vol. 135(C).

    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:13:y:2020:i:5:p:1160-:d:328223. 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.