IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i23p7820-d1289479.html
   My bibliography  Save this article

A Feasibility Study of Profiting from System Imbalance Using Residential Electric Vehicle Charging Infrastructure

Author

Listed:
  • Marián Tomašov

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Power Electrical Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Milan Straka

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Mathematical Methods and Operations Research, Faculty of Management Science and Informatics, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Dávid Martinko

    (Department of Electric Power Engineering, Faculty of Electrical Engineering and Informatics, Technical University of Košice, 042 00 Košice, Slovakia)

  • Peter Braciník

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Power Electrical Systems, Faculty of Electrical Engineering and Information Technology, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

  • Ľuboš Buzna

    (INO-HUB Energy j.s.a., Tomášikova 30, 821 01 Bratislava, Slovakia
    Department of Mathematical Methods and Operations Research, Faculty of Management Science and Informatics, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia
    Department of International Research Projects-ERADIATE+, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia)

Abstract

Residential chargers are going to become the standard in the near future. Their operational cycles are closely tied to users’ daily routines, and the power consumption fluctuates between zero and peak levels. These types of installations are particularly challenging for the grid, especially concerning the balance of electricity production and consumption. Using battery storage in conjunction with renewable sources (e.g., photovoltaic power plants) represents a flexible solution for grid stabilization, but it is also associated with additional costs. Nowadays, grid authorities penalize a destabilization of the grid resulting from an increased imbalance between electricity generation and consumption and reward contributions to the system balance. Hence, there is a motivation for larger prosumers to make use of this mechanism to reduce their operational costs by better aligning their energy needs with the grid. This study explores the possibility of utilizing battery storage when it is not needed to fulfil its primary function of supporting charging electric vehicles, to generate some additional profit from providing a counter-imbalance. To test this idea, we develop an optimization model that maximizes the economic profit, considering system imbalance penalties/rewards, photovoltaic production, electric vehicle charging demand, and battery storage utilization. By means of computer simulation, we assess the overall operational costs while varying key installation parameters such as battery capacity and power, the installed power of photovoltaic panels and the prediction model’s accuracy. We identify conditions when counter-imbalance has proven to be a viable way to reduce installation costs. These conditions include temporal distribution of charging demand, electricity prices and photovoltaic production. For the morning time window, with a suitable setting of the installation parameters, the cost reduction reaches up to 14% compared to the situation without counter-imbalance.

Suggested Citation

  • Marián Tomašov & Milan Straka & Dávid Martinko & Peter Braciník & Ľuboš Buzna, 2023. "A Feasibility Study of Profiting from System Imbalance Using Residential Electric Vehicle Charging Infrastructure," Energies, MDPI, vol. 16(23), pages 1-27, November.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:23:p:7820-:d:1289479
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/23/7820/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/23/7820/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eicke, Anselm & Ruhnau, Oliver & Hirth, Lion, 2021. "Electricity balancing as a market equilibrium: An instrument-based estimation of supply and demand for imbalance energy," Energy Economics, Elsevier, vol. 102(C).
    2. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    3. Carlo Corinaldesi & Georg Lettner & Daniel Schwabeneder & Amela Ajanovic & Hans Auer, 2020. "Impact of Different Charging Strategies for Electric Vehicles in an Austrian Office Site," Energies, MDPI, vol. 13(22), pages 1-17, November.
    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. Md Jamal Ahmed Shohan & Md Maidul Islam & Sophia Owais & Md Omar Faruque, 2024. "Optimal Energy Management of EVs at Workplaces and Residential Buildings Using Heuristic Graph-Search Algorithm," Energies, MDPI, vol. 17(21), pages 1-20, 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. Luiz Almeida & Ana Soares & Pedro Moura, 2023. "A Systematic Review of Optimization Approaches for the Integration of Electric Vehicles in Public Buildings," Energies, MDPI, vol. 16(13), pages 1-26, June.
    2. Yang, Jie & Yu, Fan & Ma, Kai & Yang, Bo & Yue, Zhiyuan, 2024. "Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles," Renewable Energy, Elsevier, vol. 224(C).
    3. Duan, Ditao & Poursoleiman, Roza, 2021. "Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging station," Utilities Policy, Elsevier, vol. 72(C).
    4. Lei Yao & Chongtao Bai & Hao Fu & Suhua Lou & Yan Fu, 2023. "Optimization of Expressway Microgrid Construction Mode and Capacity Configuration Considering Carbon Trading," Energies, MDPI, vol. 16(18), pages 1-17, September.
    5. Andriosopoulos, Kostas & Bigerna, Simona & Bollino, Carlo Andrea & Micheli, Silvia, 2018. "The impact of age on Italian consumers' attitude toward alternative fuel vehicles," Renewable Energy, Elsevier, vol. 119(C), pages 299-308.
    6. Zhiwen Zhang & Jie Tang & Jiyuan Zhang & Tianci Zhang, 2024. "Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle," Energies, MDPI, vol. 17(6), pages 1-22, March.
    7. Aminu Bugaje & Mathias Ehrenwirth & Christoph Trinkl & Wilfried Zörner, 2021. "Electric Two-Wheeler Vehicle Integration into Rural Off-Grid Photovoltaic System in Kenya," Energies, MDPI, vol. 14(23), pages 1-27, November.
    8. Mehrjerdi, Hasan & Bornapour, Mosayeb & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh, 2019. "Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes," Energy, Elsevier, vol. 168(C), pages 919-930.
    9. Christian Montaleza & Paul Arévalo & Jimmy Gallegos & Francisco Jurado, 2024. "Enhancing Energy Management Strategies for Extended-Range Electric Vehicles through Deep Q-Learning and Continuous State Representation," Energies, MDPI, vol. 17(2), pages 1-21, January.
    10. Abu Bakar Siddique & Hossam A. Gabbar, 2023. "Adaptive Mixed-Integer Linear Programming-Based Energy Management System of Fast Charging Station with Nuclear–Renewable Hybrid Energy System," Energies, MDPI, vol. 16(2), pages 1-22, January.
    11. Subhojit Dawn & Gummadi Srinivasa Rao & M. L. N. Vital & K. Dhananjay Rao & Faisal Alsaif & Mohammed H. Alsharif, 2023. "Profit Extension of a Wind-Integrated Competitive Power System by Vehicle-to-Grid Integration and UPFC Placement," Energies, MDPI, vol. 16(18), pages 1-24, September.
    12. Mohd Bilal & Ibrahim Alsaidan & Muhannad Alaraj & Fahad M. Almasoudi & Mohammad Rizwan, 2022. "Techno-Economic and Environmental Analysis of Grid-Connected Electric Vehicle Charging Station Using AI-Based Algorithm," Mathematics, MDPI, vol. 10(6), pages 1-40, March.
    13. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    14. Pannee Suanpang & Pitchaya Jamjuntr, 2024. "Optimal Electric Vehicle Battery Management Using Q-learning for Sustainability," Sustainability, MDPI, vol. 16(16), pages 1-50, August.
    15. Mittelviefhaus, Moritz & Pareschi, Giacomo & Allan, James & Georges, Gil & Boulouchos, Konstantinos, 2021. "Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation," Applied Energy, Elsevier, vol. 301(C).
    16. Mehrjerdi, Hasan & Hemmati, Reza, 2020. "Coordination of vehicle-to-home and renewable capacity resources for energy management in resilience and self-healing building," Renewable Energy, Elsevier, vol. 146(C), pages 568-579.
    17. Aqib Shafiq & Sheeraz Iqbal & Salman Habib & Atiq ur Rehman & Anis ur Rehman & Ali Selim & Emad M. Ahmed & Salah Kamel, 2022. "Solar PV-Based Electric Vehicle Charging Station for Security Bikes: A Techno-Economic and Environmental Analysis," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    18. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    19. George-Williams, H. & Wade, N. & Carpenter, R.N., 2022. "A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    20. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Zhou, Yuekuan & Mansouri, Seyed Amir & Jurado, Francisco, 2024. "Best-case-aware planning of photovoltaic-battery systems for multi-mode charging stations," Renewable Energy, Elsevier, vol. 225(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:16:y:2023:i:23:p:7820-:d:1289479. 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.