IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i9p2315-d354658.html
   My bibliography  Save this article

Virtual Storage-Based Model for Estimation of Economic Benefits of Electric Vehicles in Renewable Portfolios

Author

Listed:
  • Josip Vasilj

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia)

  • Damir Jakus

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia)

  • Petar Sarajcev

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia)

Abstract

The expected increase in the presence of electric vehicles raises numerous questions regarding their impact on the market relations. Depending on the agreement between the involved parties, the position of EVs changes from passive (traditional role) to active. Active EVs are beneficial for variability and uncertainty-intense modern power systems. To enable this transition, a suitable framework in the form of agreements is required in order to establish the terms and responsibilities. Following the presented agreements, we propose a novel method for evaluation of the benefits that the newly added EVs bring to the portfolio. The method comprises two steps, a Monte Carlo simulation of the EV driving/charging patterns and an optimization model for market related decision making. The method results in the estimates on economic savings resulting from adding EVs to portfolios. An illustrative example is used in order to give an idea of the range of the benefits.

Suggested Citation

  • Josip Vasilj & Damir Jakus & Petar Sarajcev, 2020. "Virtual Storage-Based Model for Estimation of Economic Benefits of Electric Vehicles in Renewable Portfolios," Energies, MDPI, vol. 13(9), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2315-:d:354658
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/9/2315/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/9/2315/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Muhammad Huda & Tokimatsu Koji & Muhammad Aziz, 2020. "Techno Economic Analysis of Vehicle to Grid (V2G) Integration as Distributed Energy Resources in Indonesia Power System," Energies, MDPI, vol. 13(5), pages 1-16, March.
    2. Vasilj, J. & Sarajcev, P. & Jakus, D., 2016. "Estimating future balancing power requirements in wind–PV power system," Renewable Energy, Elsevier, vol. 99(C), pages 369-378.
    3. Olauson, Jon & Bergkvist, Mikael, 2016. "Correlation between wind power generation in the European countries," Energy, Elsevier, vol. 114(C), pages 663-670.
    4. Ângelo Casaleiro & Rodrigo Amaro e Silva & João Serra, 2020. "Plug-in Electric Vehicles for Grid Services Provision: Proposing an Operational Characterization Procedure for V2G Systems," Energies, MDPI, vol. 13(5), pages 1-12, March.
    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. Alicia Triviño & José M. González-González & José A. Aguado, 2021. "Wireless Power Transfer Technologies Applied to Electric Vehicles: A Review," Energies, MDPI, vol. 14(6), pages 1-21, March.

    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. Niklas Andersen & Ola Eriksson & Karl Hillman & Marita Wallhagen, 2016. "Wind Turbines’ End-of-Life: Quantification and Characterisation of Future Waste Materials on a National Level," Energies, MDPI, vol. 9(12), pages 1-24, November.
    2. Lindberg, O. & Lingfors, D. & Arnqvist, J., 2022. "Analyzing the mechanisms behind temporal correlation between power sources using frequency separated time scales: A Swedish case study on PV and wind," Energy, Elsevier, vol. 259(C).
    3. Li, Ying & Huang, Yuping & Liang, Yu & Song, Chenxi & Liao, Suliang, 2024. "Economic and carbon reduction potential assessment of vehicle-to-grid development in guangdong province," Energy, Elsevier, vol. 302(C).
    4. Daniele Menniti & Anna Pinnarelli & Nicola Sorrentino & Pasquale Vizza & Giovanni Brusco & Giuseppe Barone & Gianluca Marano, 2022. "Techno Economic Analysis of Electric Vehicle Grid Integration Aimed to Provide Network Flexibility Services in Italian Regulatory Framework," Energies, MDPI, vol. 15(7), pages 1-34, March.
    5. Mohammad Shahjalal & Tamanna Shams & Moshammed Nishat Tasnim & Md Rishad Ahmed & Mominul Ahsan & Julfikar Haider, 2022. "A Critical Review on Charging Technologies of Electric Vehicles," Energies, MDPI, vol. 15(21), pages 1-26, November.
    6. Naemi, Mostafa & Brear, Michael J., 2020. "A hierarchical, physical and data-driven approach to wind farm modelling," Renewable Energy, Elsevier, vol. 162(C), pages 1195-1207.
    7. Titz, Maurizio & Pütz, Sebastian & Witthaut, Dirk, 2024. "Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI," Applied Energy, Elsevier, vol. 356(C).
    8. Walter, Viktor & Göransson, Lisa, 2022. "Trade as a variation management strategy for wind and solar power integration," Energy, Elsevier, vol. 238(PA).
    9. Krzysztof Zagrajek, 2021. "A Survey Data Approach for Determining the Probability Values of Vehicle-to-Grid Service Provision," Energies, MDPI, vol. 14(21), pages 1-38, November.
    10. Berger, Mathias & Radu, David & Fonteneau, Raphaël & Henry, Robin & Glavic, Mevludin & Fettweis, Xavier & Le Du, Marc & Panciatici, Patrick & Balea, Lucian & Ernst, Damien, 2020. "Critical time windows for renewable resource complementarity assessment," Energy, Elsevier, vol. 198(C).
    11. Jamiu O. Oladigbolu & Asad Mujeeb & Amir A. Imam & Ali Muhammad Rushdi, 2022. "Design, Technical and Economic Optimization of Renewable Energy-Based Electric Vehicle Charging Stations in Africa: The Case of Nigeria," Energies, MDPI, vol. 16(1), pages 1-32, December.
    12. Rahman, Md Mustafizur & Gemechu, Eskinder & Oni, Abayomi Olufemi & Kumar, Amit, 2023. "The development of a techno-economic model for assessment of cost of energy storage for vehicle-to-grid applications in a cold climate," Energy, Elsevier, vol. 262(PA).
    13. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Lu, Jia & Cheng, Chuntian, 2023. "Short-term coordinated hybrid hydro-wind-solar optimal scheduling model considering multistage section restrictions," Renewable Energy, Elsevier, vol. 217(C).
    14. Bogdanov, Dmitrii & Breyer, Christian, 2024. "Role of smart charging of electric vehicles and vehicle-to-grid in integrated renewables-based energy systems on country level," Energy, Elsevier, vol. 301(C).
    15. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    16. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    17. Jouttijärvi, Sami & Lobaccaro, Gabriele & Kamppinen, Aleksi & Miettunen, Kati, 2022. "Benefits of bifacial solar cells combined with low voltage power grids at high latitudes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    18. Tianyao Zhang & Diyi Chen & Jing Liu & Beibei Xu & Venkateshkumar M, 2020. "A Feasibility Analysis of Controlling a Hybrid Power System over Short Time Intervals," Energies, MDPI, vol. 13(21), pages 1-21, October.
    19. Nordström, Henrik & Söder, Lennart & Eriksson, Robert, 2024. "Continuous power imbalance assessment from multi-area economic dispatch models," Renewable Energy, Elsevier, vol. 225(C).
    20. Bilal, Mohd & Ahmad, Fareed & Mohammad, Arshad & Rizwan, Mohammad, 2025. "Techno-economic evaluation and sensitivity analysis of renewable energy based designing of plug-in electric vehicle load considering load following strategy," Applied Energy, Elsevier, vol. 377(PC).

    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:9:p:2315-:d:354658. 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.