IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p9023-d987465.html
   My bibliography  Save this article

Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers

Author

Listed:
  • Akansha Jain

    (Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA)

  • Masoud Karimi-Ghartemani

    (Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA)

Abstract

As the world is transitioning to electric vehicles (EVs), the existing power grids are facing several challenges. In particular, the additional charging power demand may repeatedly overload the traditionally-sized distribution transformers and adversely impact their operational life. To address this challenge, this paper proposes an EV-based reactive power compensation strategy for transformer overloading mitigation. Specifically, a low-bandwidth centralized recursive controller is proposed to determine a set point for the EV’s onboard charger’s reactive power. Importantly, the proposed strategy is practically implementable in existing distribution grids as it does not rely on smart grid infrastructure and is stable under potential communication delays and partial failures. This paper discusses the controller’s structure, design, and stability in detail. The proposed solution is tested with a realistic secondary distribution system considering four different EV charging scenarios with both Level 1 and Level 2 residential EV charging. Specifically, IEEE Standard C57.91-2011 is used to quantify the impact of EV charging on the transformer’s life. It is shown that with the proposed method, transformer overloading is significantly reduced, and the transformer’s life improves by an average of 47% over a year in all four scenarios.

Suggested Citation

  • Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9023-:d:987465
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/9023/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/23/9023/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shang, Yitong & Liu, Man & Shao, Ziyun & Jian, Linni, 2020. "Internet of smart charging points with photovoltaic Integration: A high-efficiency scheme enabling optimal dispatching between electric vehicles and power grids," Applied Energy, Elsevier, vol. 278(C).
    2. Muratori, Matteo & Moran, Michael J. & Serra, Emmanuele & Rizzoni, Giorgio, 2013. "Highly-resolved modeling of personal transportation energy consumption in the United States," Energy, Elsevier, vol. 58(C), pages 168-177.
    3. Steffen Limmer, 2019. "Dynamic Pricing for Electric Vehicle Charging—A Literature Review," Energies, MDPI, vol. 12(18), pages 1-24, September.
    4. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    5. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Zheng, Yanchong & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2019. "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 424-439.
    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. Shimi Sudha Letha & Math H. J. Bollen & Tatiano Busatto & Angela Espin Delgado & Enock Mulenga & Hamed Bakhtiari & Jil Sutaria & Kazi Main Uddin Ahmed & Naser Nakhodchi & Selçuk Sakar & Vineetha Ravin, 2023. "Power Quality Issues of Electro-Mobility on Distribution Network—An Overview," Energies, MDPI, vol. 16(13), pages 1-21, June.
    2. Dorian O. Sidea & Andrei M. Tudose & Irina I. Picioroaga & Constantin Bulac, 2022. "Two-Stage Optimal Active-Reactive Power Coordination for Microgrids with High Renewable Sources Penetration and Electrical Vehicles Based on Improved Sine−Cosine Algorithm," Mathematics, MDPI, vol. 11(1), pages 1-24, December.
    3. Amanda M. P. Barros & Jorge H. Angelim & Carolina M. Affonso, 2023. "Impact on Distribution Transformer Life Using Electric Vehicles with Long-Range Battery Capacity," Energies, MDPI, vol. 16(12), pages 1-13, June.

    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. Syed Taha Taqvi & Ali Almansoori & Azadeh Maroufmashat & Ali Elkamel, 2022. "Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach," Energies, MDPI, vol. 15(24), pages 1-21, December.
    2. Nam Hoai Nguyen & Quynh T. Tran & Thao V. Nguyen & Nam Tran & Leon Roose & Saeed Sepasi & Maria Luisa Di Silvestre, 2023. "A Method for Assessing the Feasibility of Integrating Planned Unidirectional EV Chargers into the Distribution Grid: A Case Study in Danang, Vietnam," Energies, MDPI, vol. 16(9), pages 1-16, April.
    3. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2022. "Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange," Applied Energy, Elsevier, vol. 310(C).
    4. Tang, Yanyan & Zhang, Qi & Mclellan, Benjamin & Li, Hailong, 2018. "Study on the impacts of sharing business models on economic performance of distributed PV-Battery systems," Energy, Elsevier, vol. 161(C), pages 544-558.
    5. Ma, Shao-Chao & Yi, Bo-Wen & Fan, Ying, 2022. "Research on the valley-filling pricing for EV charging considering renewable power generation," Energy Economics, Elsevier, vol. 106(C).
    6. Sanchari Deb, 2021. "Machine Learning for Solving Charging Infrastructure Planning Problems: A Comprehensive Review," Energies, MDPI, vol. 14(23), pages 1-19, November.
    7. 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).
    8. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    9. Alqahtani, Mohammed & Hu, Mengqi, 2022. "Dynamic energy scheduling and routing of multiple electric vehicles using deep reinforcement learning," Energy, Elsevier, vol. 244(PA).
    10. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    11. Moe Soheilian & Géza Fischl & Myriam Aries, 2021. "Smart Lighting Application for Energy Saving and User Well-Being in the Residential Environment," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    12. Klaus Ackermann & Simon D Angus & Paul A Raschky, 2020. "Estimating Sleep and Work Hours from Alternative Data by Segmented Functional Classification Analysis, SFCA," SoDa Laboratories Working Paper Series 2020-04, Monash University, SoDa Laboratories.
    13. Prince Waqas Khan & Yung-Cheol Byun, 2021. "Blockchain-Based Peer-to-Peer Energy Trading and Charging Payment System for Electric Vehicles," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    14. Dingyi Lu & Yunqian Lu & Kexin Zhang & Chuyuan Zhang & Shao-Chao Ma, 2023. "An Application Designed for Guiding the Coordinated Charging of Electric Vehicles," Sustainability, MDPI, vol. 15(14), pages 1-16, July.
    15. Orsi, Francesco & Muratori, Matteo & Rocco, Matteo & Colombo, Emanuela & Rizzoni, Giorgio, 2016. "A multi-dimensional well-to-wheels analysis of passenger vehicles in different regions: Primary energy consumption, CO2 emissions, and economic cost," Applied Energy, Elsevier, vol. 169(C), pages 197-209.
    16. Fan, Jin & Li, Jun & Wu, Yanrui & Wang, Shanyong & Zhao, Dingtao, 2016. "The effects of allowance price on energy demand under a personal carbon trading scheme," Applied Energy, Elsevier, vol. 170(C), pages 242-249.
    17. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    18. Klaus Ackermann & Simon D. Angus & Paul A. Raschky, 2020. "Estimating Sleep & Work Hours from Alternative Data by Segmented Functional Classification Analysis (SFCA)," Papers 2010.08102, arXiv.org.
    19. Huang, Yunyou & Zhan, Jianfeng & Luo, Chunjie & Wang, Lei & Wang, Nana & Zheng, Daoyi & Fan, Fanda & Ren, Rui, 2019. "An electricity consumption model for synthesizing scalable electricity load curves," Energy, Elsevier, vol. 169(C), pages 674-683.
    20. Fescioglu-Unver, Nilgun & Yıldız Aktaş, Melike, 2023. "Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(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:15:y:2022:i:23:p:9023-:d:987465. 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.