IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1746-d759266.html
   My bibliography  Save this article

A Novel Smart Charging Method to Mitigate Voltage Fluctuation at Fast Charging Stations

Author

Listed:
  • Sami M. Alshareef

    (Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia)

Abstract

The research presented in this paper focuses on the impact of fast charging stations (FCSs) on voltage quality. When the operation of FCSs causes a voltage fluctuation and light flicker, the FCSs may be disconnected, as per the utility general standard practice, which results in financial loss represented by FCS downtime. FCS downtime can be avoided by mitigating voltage fluctuation and light flicker. Flicker mitigation devices that are available in the market are characterized by their high total annual equivalent costs. As an alternative, a novel smart charging method is proposed in this study in order to mitigate both voltage fluctuation and light flicker, whereby customers can select one of three charging services available in fast chargers: premium, regular, or economic charging power. The charging power is selected according to customer priority in relation to time and cost, which offers more flexibility than those currently available in the literature. For instance, the premium power can be selected if the time is more valuable to the customer at the time of arrival at the FCS; in contrast, the regular or economic power are utilized if the cost is more valuable than the time. The results reveal that when an FCS charges a vehicle by an uncontrolled charging method, the FCS violates the flicker tolerance especially when demand for its service is increased by 20% and beyond. In contrast, the flicker limit is not violated when vehicles are charged from an FCS as per the proposed smart charging approach, even when the penetration on the FCS is increased by 50%. The proposed smart charging method offers a compromise solution to satisfy several stakeholders with different interests. Thus, the system operator equipment, FCS investors, nearby customers, and owners of electric vehicles will not be impacted by integrating the FCSs into the distribution networks.

Suggested Citation

  • Sami M. Alshareef, 2022. "A Novel Smart Charging Method to Mitigate Voltage Fluctuation at Fast Charging Stations," Energies, MDPI, vol. 15(5), pages 1-25, February.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1746-:d:759266
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1746/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/5/1746/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Perera, D. & Meegahapola, L. & Perera, S. & Ciufo, P., 2014. "Characterisation of flicker emission and propagation in distribution networks with bi-directional power flows," Renewable Energy, Elsevier, vol. 63(C), pages 172-180.
    2. van der Kam, Mart & van Sark, Wilfried, 2015. "Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; a case study," Applied Energy, Elsevier, vol. 152(C), pages 20-30.
    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. Sami M. Alshareef, 2022. "A Novel Fairness-Based Cost Model for Adopting Smart Charging at Fast Charging Stations," Sustainability, MDPI, vol. 14(11), pages 1-28, May.
    2. Nnaemeka Vincent Emodi & Scott Dwyer & Kriti Nagrath & John Alabi, 2022. "Electromobility in Australia: Tariff Design Structure and Consumer Preferences for Mobile Distributed Energy Storage," Sustainability, MDPI, vol. 14(11), pages 1-18, May.

    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. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    2. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
    3. Shi, Ruifeng & Li, Shaopeng & Zhang, Penghui & Lee, Kwang Y., 2020. "Integration of renewable energy sources and electric vehicles in V2G network with adjustable robust optimization," Renewable Energy, Elsevier, vol. 153(C), pages 1067-1080.
    4. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    5. Lefeng, Shi & Shengnan, Lv & Chunxiu, Liu & Yue, Zhou & Cipcigan, Liana & Acker, Thomas L., 2020. "A framework for electric vehicle power supply chain development," Utilities Policy, Elsevier, vol. 64(C).
    6. Igual, R. & Medrano, C., 2020. "Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    7. Kuang, Yanqing & Chen, Yang & Hu, Mengqi & Yang, Dong, 2017. "Influence analysis of driver behavior and building category on economic performance of electric vehicle to grid and building integration," Applied Energy, Elsevier, vol. 207(C), pages 427-437.
    8. Varone, Alberto & Heilmann, Zeno & Porruvecchio, Guido & Romanino, Alessandro, 2024. "Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    9. Brinkel, N.B.G. & Schram, W.L. & AlSkaif, T.A. & Lampropoulos, I. & van Sark, W.G.J.H.M., 2020. "Should we reinforce the grid? Cost and emission optimization of electric vehicle charging under different transformer limits," Applied Energy, Elsevier, vol. 276(C).
    10. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    11. Ruben Garruto & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "Connecting Parking Facilities to the Electric Grid: A Vehicle-to-Grid Feasibility Study in a Railway Station’s Car Park," Energies, MDPI, vol. 13(12), pages 1-23, June.
    12. Wang, Shouxiang & Chen, Haiwen, 2019. "A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network," Applied Energy, Elsevier, vol. 235(C), pages 1126-1140.
    13. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    14. Mousavizade, Mirsaeed & Bai, Feifei & Garmabdari, Rasoul & Sanjari, Mohammad & Taghizadeh, Foad & Mahmoudian, Ali & Lu, Junwei, 2023. "Adaptive control of V2Gs in islanded microgrids incorporating EV owner expectations," Applied Energy, Elsevier, vol. 341(C).
    15. Monika Topel & Josefine Grundius, 2020. "Load Management Strategies to Increase Electric Vehicle Penetration—Case Study on a Local Distribution Network in Stockholm," Energies, MDPI, vol. 13(18), pages 1-16, September.
    16. Brok, Niclas Brabrand & Munk-Nielsen, Thomas & Madsen, Henrik & Stentoft, Peter A., 2020. "Unlocking energy flexibility of municipal wastewater aeration using predictive control to exploit price differences in power markets," Applied Energy, Elsevier, vol. 280(C).
    17. Sami M. Alshareef, 2022. "A Novel Fairness-Based Cost Model for Adopting Smart Charging at Fast Charging Stations," Sustainability, MDPI, vol. 14(11), pages 1-28, May.
    18. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2017. "Integrating renewable energy sources by electric vehicle fleets under uncertainty," Energy, Elsevier, vol. 141(C), pages 2145-2153.
    19. Li, Yang & Yang, Zhen & Li, Guoqing & Mu, Yunfei & Zhao, Dongbo & Chen, Chen & Shen, Bo, 2018. "Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing," Applied Energy, Elsevier, vol. 232(C), pages 54-68.
    20. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M. & Lund, Peter D., 2019. "Energy integration and interaction between buildings and vehicles: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.

    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:5:p:1746-:d:759266. 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.