IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v8y2015i3p1760-1783d46351.html
   My bibliography  Save this article

MV and LV Residential Grid Impact of Combined Slow and Fast Charging of Electric Vehicles

Author

Listed:
  • Niels Leemput

    (Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium)

  • Frederik Geth

    (Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium)

  • Juan Van Roy

    (Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium)

  • Pol Olivella-Rosell

    (Centre of Technological Innovation in Static Converters and Drives, Department of Electrical Engineering, College of Industrial Engineering of Barcelona, Universitat Politècnica de Catalunya-BarcelonaTech, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain)

  • Johan Driesen

    (Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium)

  • Andreas Sumper

    (Centre of Technological Innovation in Static Converters and Drives, Department of Electrical Engineering, College of Industrial Engineering of Barcelona, Universitat Politècnica de Catalunya-BarcelonaTech, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain)

Abstract

This article investigates the combined low voltage (LV) and medium voltage (MV) residential grid impact for slow and fast electric vehicle (EV) charging, for an increasing local penetration rate and for different residential slow charging strategies. A realistic case study for a Flemish urban distribution grid is used, for which three residential slow charging strategies are modeled: uncoordinated charging, residential off-peak charging, and EV-based peak shaving. For each slow charging strategy, the EV hosting capacity is determined, with and without the possibility of fast charging, while keeping the grid within its operating limits. The results show that the distribution grid impact is much less sensitive to the presence of fast charging compared to the slow charging strategy. EV-based peak shaving results in the lowest grid impact, allowing for the highest EV hosting capacity. Residential off-peak charging has the highest grid impact, due the load synchronization effect that occurs, resulting in the lowest EV hosting capacity. Therefore, the EV users should be incentivized to charge their EVs in a more grid-friendly manner when the local EV penetration rate becomes significant, as this increases the EV hosting capacity much more than the presence of fast charging decreases it.

Suggested Citation

  • Niels Leemput & Frederik Geth & Juan Van Roy & Pol Olivella-Rosell & Johan Driesen & Andreas Sumper, 2015. "MV and LV Residential Grid Impact of Combined Slow and Fast Charging of Electric Vehicles," Energies, MDPI, vol. 8(3), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:3:p:1760-1783:d:46351
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/8/3/1760/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/8/3/1760/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lyon, Thomas P. & Michelin, Mark & Jongejan, Arie & Leahy, Thomas, 2012. "Is “smart charging” policy for electric vehicles worthwhile?," Energy Policy, Elsevier, vol. 41(C), pages 259-268.
    2. Schroeder, Andreas & Traber, Thure, 2012. "The economics of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 43(C), pages 136-144.
    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. Su Su & Yong Hu & Tiantian Yang & Shidan Wang & Ziqi Liu & Xiangxiang Wei & Mingchao Xia & Yutaka Ota & Koji Yamashita, 2018. "Research on an Electric Vehicle Owner-Friendly Charging Strategy Using Photovoltaic Generation at Office Sites in Major Chinese Cities," Energies, MDPI, vol. 11(2), pages 1-19, February.
    2. Viktor Slednev & Patrick Jochem & Wolf Fichtner, 2022. "Impacts of electric vehicles on the European high and extra high voltage power grid," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 824-837, June.
    3. Mingchao Xia & Qingying Lai & Yajiao Zhong & Canbing Li & Hsiao-Dong Chiang, 2016. "Aggregator-Based Interactive Charging Management System for Electric Vehicle Charging," Energies, MDPI, vol. 9(3), pages 1-14, March.
    4. Sandström, Maria & Huang, Pei & Bales, Chris & Dotzauer, Erik, 2023. "Evaluation of hosting capacity of the power grid for electric vehicles – A case study in a Swedish residential area," Energy, Elsevier, vol. 284(C).
    5. Julia Vopava & Ulrich Bergmann & Thomas Kienberger, 2020. "Synergies between e-Mobility and Photovoltaic Potentials—A Case Study on an Urban Medium Voltage Grid," Energies, MDPI, vol. 13(15), pages 1-29, July.
    6. Resch, Matthias & Bühler, Jochen & Klausen, Mira & Sumper, Andreas, 2017. "Impact of operation strategies of large scale battery systems on distribution grid planning in Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1042-1063.
    7. Sylvester Johansson & Jonas Persson & Stavros Lazarou & Andreas Theocharis, 2019. "Investigation of the Impact of Large-Scale Integration of Electric Vehicles for a Swedish Distribution Network," Energies, MDPI, vol. 12(24), pages 1-22, December.
    8. Bishnu P. Bhattarai & Kurt S. Myers & Birgitte Bak-Jensen & Sumit Paudyal, 2017. "Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks," Energies, MDPI, vol. 10(1), pages 1-18, January.
    9. Paul Stewart & Chris Bingham, 2016. "Electrical Power and Energy Systems for Transportation Applications," Energies, MDPI, vol. 9(7), pages 1-3, July.
    10. Beaufils, Timothé & Pineau, Pierre-Olivier, 2019. "Assessing the impact of residential load profile changes on electricity distribution utility revenues under alternative rate structures," Utilities Policy, Elsevier, vol. 61(C).
    11. Math H. J. Bollen & Sarah K. Rönnberg, 2017. "Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment," Energies, MDPI, vol. 10(9), pages 1-28, September.

    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. Fetene, Gebeyehu M. & Hirte, Georg & Kaplan, Sigal & Prato, Carlo G. & Tscharaktschiew, Stefan, 2016. "The economics of workplace charging," Transportation Research Part B: Methodological, Elsevier, vol. 88(C), pages 93-118.
    2. Armstrong, M. & El Hajj Moussa, C. & Adnot, J. & Galli, A. & Riviere, P., 2013. "Optimal recharging strategy for battery-switch stations for electric vehicles in France," Energy Policy, Elsevier, vol. 60(C), pages 569-582.
    3. Bonges, Henry A. & Lusk, Anne C., 2016. "Addressing electric vehicle (EV) sales and range anxiety through parking layout, policy and regulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 63-73.
    4. 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.
    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. Bellekom, Sandra & Benders, René & Pelgröm, Steef & Moll, Henk, 2012. "Electric cars and wind energy: Two problems, one solution? A study to combine wind energy and electric cars in 2020 in The Netherlands," Energy, Elsevier, vol. 45(1), pages 859-866.
    7. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    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. Hennings, Wilfried & Mischinger, Stefan & Linssen, Jochen, 2013. "Utilization of excess wind power in electric vehicles," Energy Policy, Elsevier, vol. 62(C), pages 139-144.
    10. Szinai, Julia K. & Sheppard, Colin J.R. & Abhyankar, Nikit & Gopal, Anand R., 2020. "Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management," Energy Policy, Elsevier, vol. 136(C).
    11. Mona Kabus & Lars Nolting & Benedict J. Mortimer & Jan C. Koj & Wilhelm Kuckshinrichs & Rik W. De Doncker & Aaron Praktiknjo, 2020. "Environmental Impacts of Charging Concepts for Battery Electric Vehicles: A Comparison of On-Board and Off-Board Charging Systems Based on a Life Cycle Assessment," Energies, MDPI, vol. 13(24), pages 1-31, December.
    12. Das, H.S. & Rahman, M.M. & Li, S. & Tan, C.W., 2020. "Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    13. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    14. Ruifeng Shi & Jiahua Liu & Zhenhong Liao & Li Niu & Eke Ibrahim & Fang Fu, 2019. "An Electric Taxi Charging Station Planning Scheme Based on an Improved Destination Choice Method," Energies, MDPI, vol. 12(19), pages 1-21, October.
    15. Brozynski, Max T. & Leibowicz, Benjamin D., 2022. "A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 755-770.
    16. 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.
    17. Wee, Sherilyn & Coffman, Makena & Allen, Scott, 2020. "EV driver characteristics: Evidence from Hawaii," Transport Policy, Elsevier, vol. 87(C), pages 33-40.
    18. 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.
    19. Seyed Ahmad Reza Mir Mohammadi Kooshknow & Rob den Exter & Franco Ruzzenenti, 2020. "An Exploratory Agent-Based Modeling Analysis Approach to Test Business Models for Electricity Storage," Energies, MDPI, vol. 13(7), pages 1-14, April.
    20. Tan, Bing Qing & Kang, Kai & Zhong, Ray Y., 2023. "Electric vehicle charging infrastructure investment strategy analysis: State-owned versus private parking lots," Transport Policy, Elsevier, vol. 141(C), pages 54-71.

    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:8:y:2015:i:3:p:1760-1783:d:46351. 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.