IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i10p3808-d821109.html
   My bibliography  Save this article

A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks

Author

Listed:
  • Despoina Kothona

    (Department of Electrical and Computer Engineering, University of Western Macedonia, Ikaron 3, Koila, 50132 Kozani, Greece)

  • Aggelos S. Bouhouras

    (Department of Electrical and Computer Engineering, University of Western Macedonia, Ikaron 3, Koila, 50132 Kozani, Greece)

Abstract

The topic of power loss reduction in distribution systems has gained significant attention over recent years. Despite the efforts of the European Union towards the minimization of power losses, the decarbonization of the transport sector has raised several concerns, since charging overlaps of Electric Vehicles (EVs) can cause extensive power losses and power quality issues. Considering these, the present paper proposes a two-stage EV charging planning and Network Reconfiguration (NR) methodology, addressing the problem of power loss minimization in both Low-Voltage (LV) and Medium-Voltage (MV) Distribution Networks (DNs), respectively. In the first stage, considering the key role of the aggregator, the EV charging planning is applied to LV DN. In the second stage, the NR technique is applied to the MV DN, by taking into account the hourly power demand of LV DNs as obtained by the aggregators. The proposed methodology has been applied on a benchmarked MV network for which each node is represented by a real LV network. The results indicate that the proposed methodology could yield up to a 63.64% power loss reduction, in respect to the base scenario, i.e., no charging planning and no NR are applied.

Suggested Citation

  • Despoina Kothona & Aggelos S. Bouhouras, 2022. "A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks," Energies, MDPI, vol. 15(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3808-:d:821109
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/10/3808/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/10/3808/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Kamran Ali Memon & Ben Horan & Anzar Mahmood & Saad Mekhilef, 2020. "An Integrated Approach to Optimal Charging Scheduling of Electric Vehicles Integrated with Improved Medium-Voltage Network Reconfiguration for Power Loss Minimization," Sustainability, MDPI, vol. 12(21), pages 1-15, November.
    2. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    3. Piotr Wróblewski & Wojciech Drożdż & Wojciech Lewicki & Jakub Dowejko, 2021. "Total Cost of Ownership and Its Potential Consequences for the Development of the Hydrogen Fuel Cell Powered Vehicle Market in Poland," Energies, MDPI, vol. 14(8), pages 1-25, April.
    4. Piotr Wróblewski & Jerzy Kupiec & Wojciech Drożdż & Wojciech Lewicki & Jarosław Jaworski, 2021. "The Economic Aspect of Using Different Plug-In Hybrid Driving Techniques in Urban Conditions," Energies, MDPI, vol. 14(12), pages 1-17, June.
    5. Morsy Nour & José Pablo Chaves-Ávila & Gaber Magdy & Álvaro Sánchez-Miralles, 2020. "Review of Positive and Negative Impacts of Electric Vehicles Charging on Electric Power Systems," Energies, MDPI, vol. 13(18), pages 1-34, September.
    6. Tu, Ran & Gai, Yijun (Jessie) & Farooq, Bilal & Posen, Daniel & Hatzopoulou, Marianne, 2020. "Electric vehicle charging optimization to minimize marginal greenhouse gas emissions from power generation," Applied Energy, Elsevier, vol. 277(C).
    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. Guillermo Alonso & Ricardo F. Alonso & Antonio Carlos Zambroni Zambroni De Souza & Walmir Freitas, 2022. "Enhanced Artificial Immune Systems and Fuzzy Logic for Active Distribution Systems Reconfiguration," Energies, MDPI, vol. 15(24), pages 1-18, December.
    2. Anant Oonsivilai & Banyat Boribun & Padej Pao-la-or, 2023. "Integration of Distributed Generation and Plug-in Electric Vehicles on Power Distribution System by Using Queuing Theory," Energies, MDPI, vol. 16(7), pages 1-15, March.

    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. Shaheer Ansari & Afida Ayob & Molla Shahadat Hossain Lipu & Aini Hussain & Mohamad Hanif Md Saad, 2021. "Multi-Channel Profile Based Artificial Neural Network Approach for Remaining Useful Life Prediction of Electric Vehicle Lithium-Ion Batteries," Energies, MDPI, vol. 14(22), pages 1-22, November.
    2. 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).
    3. Zhong, Zewei & Zeng, Yun & Zhao, Xiaoli & Zhang, Sufang, 2024. "The social benefits resulting from electric vehicle smart charging balancing economy and decarbonization," Transport Policy, Elsevier, vol. 147(C), pages 113-124.
    4. Konstantina Anastasiadou & Nikolaos Gavanas & Magda Pitsiava-Latinopoulou & Evangelos Bekiaris, 2021. "Infrastructure Planning for Autonomous Electric Vehicles, Integrating Safety and Sustainability Aspects: A Multi-Criteria Analysis Approach," Energies, MDPI, vol. 14(17), pages 1-19, August.
    5. Wu, Jiabin & Li, Qihang & Bie, Yiming & Zhou, Wei, 2024. "Location-routing optimization problem for electric vehicle charging stations in an uncertain transportation network: An adaptive co-evolutionary clustering algorithm," Energy, Elsevier, vol. 304(C).
    6. Daniel Rasbash & Kevin Joseph Dillman & Jukka Heinonen & Eyjólfur Ingi Ásgeirsson, 2023. "A National and Regional Greenhouse Gas Breakeven Assessment of EVs across North America," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
    7. Tom Elliott & Joachim Geske & Richard Green, 2022. "Business Models for Active Buildings," Energies, MDPI, vol. 15(19), pages 1-17, October.
    8. Justin Fraselle & Sabine Louise Limbourg & Laura Vidal, 2021. "Cost and Environmental Impacts of a Mixed Fleet of Vehicles," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    9. Mariusz Niekurzak & Jerzy Mikulik, 2021. "Modeling of Energy Consumption and Reduction of Pollutant Emissions in a Walking Beam Furnace Using the Expert Method—Case Study," Energies, MDPI, vol. 14(23), pages 1-22, December.
    10. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
    11. Huachun Han & Huiyu Miu & Shukang Lv & Xiaodong Yuan & Yi Pan & Fei Zeng, 2024. "Fast Charging Guidance and Pricing Strategy Considering Different Types of Electric Vehicle Users’ Willingness to Charge," Energies, MDPI, vol. 17(18), pages 1-21, September.
    12. Moshammed Nishat Tasnim & Tofael Ahmed & Monjila Afrin Dorothi & Shameem Ahmad & G. M. Shafiullah & S. M. Ferdous & Saad Mekhilef, 2023. "Voltage-Oriented Control-Based Three-Phase, Three-Leg Bidirectional AC–DC Converter with Improved Power Quality for Microgrids," Energies, MDPI, vol. 16(17), pages 1-32, August.
    13. Secinaro, Silvana & Calandra, Davide & Lanzalonga, Federico & Ferraris, Alberto, 2022. "Electric vehicles’ consumer behaviours: Mapping the field and providing a research agenda," Journal of Business Research, Elsevier, vol. 150(C), pages 399-416.
    14. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    15. Abubakr, Hussein & Lashab, Abderezak & Vasquez, Juan C. & Mohamed, Tarek Hassan & Guerrero, Josep M., 2023. "Novel V2G regulation scheme using Dual-PSS for PV islanded microgrid," Applied Energy, Elsevier, vol. 340(C).
    16. Maxwell Woody & Michael T. Craig & Parth T. Vaishnav & Geoffrey M. Lewis & Gregory A. Keoleian, 2022. "Optimizing future cost and emissions of electric delivery vehicles," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 1108-1122, June.
    17. Tomasz Jałowiec & Dariusz Grala & Piotr Maśloch & Henryk Wojtaszek & Grzegorz Maśloch & Agnieszka Wójcik-Czerniawska, 2022. "Analysis of the Implementation of Functional Hydrogen Assumptions in Poland and Germany," Energies, MDPI, vol. 15(22), pages 1-25, November.
    18. Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Haider Ali & Inam Bari & Ben Horan & Saad Mekhilef & Muhammad Asif & Saeed Ahmed & Anzar Mahmood, 2020. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network," Sustainability, MDPI, vol. 12(23), pages 1-28, December.
    19. Xu, Jiazhu & Yi, Yuqin, 2023. "Multi-microgrid low-carbon economy operation strategy considering both source and load uncertainty: A Nash bargaining approach," Energy, Elsevier, vol. 263(PB).
    20. Said Bentouba & Nadjet Zioui & Peter Breuhaus & Mahmoud Bourouis, 2023. "Overview of the Potential of Energy Harvesting Sources in Electric Vehicles," Energies, MDPI, vol. 16(13), pages 1-22, July.

    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:10:p:3808-:d:821109. 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.