IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i8p3562-d1128245.html
   My bibliography  Save this article

Predicting and Managing EV Charging Demand on Electrical Grids: A Simulation-Based Approach

Author

Listed:
  • Pramote Jaruwatanachai

    (Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

  • Yod Sukamongkol

    (Energy Engineering Department, Faculty of Engineering, Ramkhamhaeng University, Bangkok 10240, Thailand)

  • Taweesak Samanchuen

    (Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom 73170, Thailand)

Abstract

Electric vehicles (EVs) are becoming increasingly popular, and it is important for utilities to understand their charging characteristics to accurately estimate the demand on the electrical grid. In this work, we developed simulation models for different EV charging scenarios in the home sector. We used them to predict maximum demand based on the increasing penetration of EV consumers. We comprehensively reviewed the literature on EV charging technologies, battery capacity, charging situations, and the impact of EV loads. Our results suggest a method for visualizing the impact of EV charging loads by considering factors such as state of charge, arrival time, charging duration, rate of charge, maximum charging power, and involvement rate. This method can be used to model load profiles and determine the number of chargers needed to meet EV user demand. We also explored the use of a time-of-use (TOU) tariff as a demand response strategy, which encourages EV owners to charge their vehicles off-peak in order to avoid higher demand charges. Our simulation results show the effects of various charging conditions on load profiles and indicate that the current TOU price strategy can accommodate a 20% growth in EV consumers, while the alternative TOU price strategy can handle up to a 30% penetration level.

Suggested Citation

  • Pramote Jaruwatanachai & Yod Sukamongkol & Taweesak Samanchuen, 2023. "Predicting and Managing EV Charging Demand on Electrical Grids: A Simulation-Based Approach," Energies, MDPI, vol. 16(8), pages 1-22, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3562-:d:1128245
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/8/3562/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/8/3562/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Monica Alonso & Hortensia Amaris & Jean Gardy Germain & Juan Manuel Galan, 2014. "Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms," Energies, MDPI, vol. 7(4), pages 1-27, April.
    2. Mihai Rata & Gabriela Rata & Constantin Filote & Maria Simona Raboaca & Adrian Graur & Ciprian Afanasov & Andreea-Raluca Felseghi, 2019. "The ElectricalVehicle Simulator for Charging Station in Mode 3 of IEC 61851-1 Standard," Energies, MDPI, vol. 13(1), pages 1-10, December.
    3. Semen Uimonen & Matti Lehtonen, 2020. "Simulation of Electric Vehicle Charging Stations Load Profiles in Office Buildings Based on Occupancy Data," Energies, MDPI, vol. 13(21), pages 1-16, October.
    4. Mullan, Jonathan & Harries, David & Bräunl, Thomas & Whitely, Stephen, 2011. "Modelling the impacts of electric vehicle recharging on the Western Australian electricity supply system," Energy Policy, Elsevier, vol. 39(7), pages 4349-4359, July.
    5. Lai, Chun Sing & Chen, Dashen & Zhang, Jinning & Zhang, Xin & Xu, Xu & Taylor, Gareth A. & Lai, Loi Lei, 2022. "Profit maximization for large-scale energy storage systems to enable fast EV charging infrastructure in distribution networks," Energy, Elsevier, vol. 259(C).
    6. Narongkorn Uthathip & Pornrapeepat Bhasaputra & Woraratana Pattaraprakorn, 2021. "Stochastic Modelling to Analyze the Impact of Electric Vehicle Penetration in Thailand," Energies, MDPI, vol. 14(16), pages 1-23, August.
    7. 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.
    8. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeshwar Mahanta, 2018. "Impact of Electric Vehicle Charging Station Load on Distribution Network," Energies, MDPI, vol. 11(1), pages 1-25, January.
    9. José F. C. Castro & Davidson C. Marques & Luciano Tavares & Nicolau K. L. Dantas & Amanda L. Fernandes & Ji Tuo & Luiz H. A. de Medeiros & Pedro Rosas, 2022. "Energy and Demand Forecasting Based on Logistic Growth Method for Electric Vehicle Fast Charging Station Planning with PV Solar System," Energies, MDPI, vol. 15(17), pages 1-21, August.
    10. Onat, Nuri Cihat & Kucukvar, Murat & Tatari, Omer, 2015. "Conventional, hybrid, plug-in hybrid or electric vehicles? State-based comparative carbon and energy footprint analysis in the United States," Applied Energy, Elsevier, vol. 150(C), pages 36-49.
    11. 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.
    12. Hui Hwang Goh & Lian Zong & Dongdong Zhang & Wei Dai & Chee Shen Lim & Tonni Agustiono Kurniawan & Kai Chen Goh, 2022. "Orderly Charging Strategy Based on Optimal Time of Use Price Demand Response of Electric Vehicles in Distribution Network," Energies, MDPI, vol. 15(5), pages 1-25, 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. Wenping Zhang & Yiming Wang & Po Xu & Donghui Li & Baosong Liu, 2023. "Evaluation and Improvement of Backup Capacity for Household Electric Vehicle Uninterruptible Power Supply (EV-UPS) Systems," Energies, MDPI, vol. 16(12), pages 1-20, June.
    2. Wardah Afzal & Li-Ye Zhao & Guang-Zhi Chen & Yu Xue, 2023. "Hybrid Wind/PV E-Bike Charging Station: Comparison of Onshore and Offshore Systems," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    3. Ahmad Almaghrebi & Kevin James & Fares Al Juheshi & Mahmoud Alahmad, 2024. "Insights into Household Electric Vehicle Charging Behavior: Analysis and Predictive Modeling," Energies, MDPI, vol. 17(4), pages 1-20, February.

    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. Lauvergne, Rémi & Perez, Yannick & Françon, Mathilde & Tejeda De La Cruz, Alberto, 2022. "Integration of electric vehicles into transmission grids: A case study on generation adequacy in Europe in 2040," Applied Energy, Elsevier, vol. 326(C).
    2. Sanchari Deb, 2021. "Machine Learning for Solving Charging Infrastructure Planning Problems: A Comprehensive Review," Energies, MDPI, vol. 14(23), pages 1-19, November.
    3. Mahmud, Khizir & Town, Graham E. & Morsalin, Sayidul & Hossain, M.J., 2018. "Integration of electric vehicles and management in the internet of energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4179-4203.
    4. 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.
    5. Crossin, Enda & Doherty, Peter J.B., 2016. "The effect of charging time on the comparative environmental performance of different vehicle types," Applied Energy, Elsevier, vol. 179(C), pages 716-726.
    6. Hadi Suyono & Mir Toufikur Rahman & Hazlie Mokhlis & Mohamadariff Othman & Hazlee Azil Illias & Hasmaini Mohamad, 2019. "Optimal Scheduling of Plug-in Electric Vehicle Charging Including Time-of-Use Tariff to Minimize Cost and System Stress," Energies, MDPI, vol. 12(8), pages 1-21, April.
    7. Huang, Bing & Meijssen, Aart Gerard & Annema, Jan Anne & Lukszo, Zofia, 2021. "Are electric vehicle drivers willing to participate in vehicle-to-grid contracts? A context-dependent stated choice experiment," Energy Policy, Elsevier, vol. 156(C).
    8. Kumar Sunil & Jayaswal, Sachin & Garg, Amit, 2018. "Charging infrastructure optimization for electric buses using mixed integer linear programming," IIMA Working Papers WP 2018-12-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    10. Haidar, Ahmed M.A. & Muttaqi, Kashem & Sutanto, Danny, 2015. "Smart Grid and its future perspectives in Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1375-1389.
    11. Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
    12. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    13. Pedro Faria & Zita Vale, 2022. "Realistic Load Modeling for Efficient Consumption Management Using Real-Time Simulation and Power Hardware-in-the-Loop," Energies, MDPI, vol. 16(1), pages 1-15, December.
    14. 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.
    15. Chitchai Srithapon & Prasanta Ghosh & Apirat Siritaratiwat & Rongrit Chatthaworn, 2020. "Optimization of Electric Vehicle Charging Scheduling in Urban Village Networks Considering Energy Arbitrage and Distribution Cost," Energies, MDPI, vol. 13(2), pages 1-20, January.
    16. Graabak, Ingeborg & Wu, Qiuwei & Warland, Leif & Liu, Zhaoxi, 2016. "Optimal planning of the Nordic transmission system with 100% electric vehicle penetration of passenger cars by 2050," Energy, Elsevier, vol. 107(C), pages 648-660.
    17. José M. Cansino & Antonio Sánchez-Braza & Teresa Sanz-Díaz, 2018. "Policy Instruments to Promote Electro-Mobility in the EU28: A Comprehensive Review," Sustainability, MDPI, vol. 10(7), pages 1-27, July.
    18. Sajjad Haider & Peter Schegner, 2020. "Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid," Energies, MDPI, vol. 13(22), pages 1-19, November.
    19. Zhang, Tong & Burke, Paul J. & Wang, Qi, 2024. "Effectiveness of electric vehicle subsidies in China: A three-dimensional panel study," Resource and Energy Economics, Elsevier, vol. 76(C).
    20. Yin, Rumeng & He, Jiang, 2023. "Design of a photovoltaic electric bike battery-sharing system in public transit stations," Applied Energy, Elsevier, vol. 332(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:8:p:3562-:d:1128245. 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.