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An Online Coordinated Charging/Discharging Strategy of Plug-in Electric Vehicles in Unbalanced Active Distribution Networks with Ancillary Reactive Service in the Energy Market

Author

Listed:
  • Nasim Jabalameli

    (Department of Electrical and Computer Engineering, Curtin University, Perth 6102, Australia)

  • Xianging Su

    (College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Sara Deilami

    (Department of Electrical and Computer Engineering, Curtin University, Perth 6102, Australia)

Abstract

The global acceptance and off-grid charging of plug-in electric vehicles (PEVs) are expected to grow tremendously in the next few years. Uncoordinated PEV charging can cause serious grid issues such as overloading of transformers and unacceptable voltage drops. Single-phase residential charging can also initiate or contribute to voltage unbalance conditions in the distribution networks. A potential solution and key challenge for PEV integration is shifting of the charging activities to off-peak periods. This paper proposes a new PEV coordination approach based on genetic algorithm (GA) optimization to perform online centralized charging and discharging considering transformer loading and node voltage magnitude and unbalance profiles. It allows PEV as source of active and reactive power to participate in energy market based on different prices during a day, without any degradation. Finally, the impacts of uncoordinated and the proposed GA coordinated PEV charging/discharging strategy are simulated for a real unbalanced Western Australian distribution network in the Perth solar city over 24 h.

Suggested Citation

  • Nasim Jabalameli & Xianging Su & Sara Deilami, 2019. "An Online Coordinated Charging/Discharging Strategy of Plug-in Electric Vehicles in Unbalanced Active Distribution Networks with Ancillary Reactive Service in the Energy Market," Energies, MDPI, vol. 12(7), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1350-:d:220986
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    References listed on IDEAS

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    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. Lund, Henrik & Kempton, Willett, 2008. "Integration of renewable energy into the transport and electricity sectors through V2G," Energy Policy, Elsevier, vol. 36(9), pages 3578-3587, September.
    3. Schleicher-Tappeser, Ruggero, 2012. "How renewables will change electricity markets in the next five years," Energy Policy, Elsevier, vol. 48(C), pages 64-75.
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    Cited by:

    1. Argo Rosin & Imre Drovtar & Heigo Mõlder & Kaija Haabel & Victor Astapov & Toomas Vinnal & Tarmo Korõtko, 2022. "Analysis of Traditional and Alternative Methods for Solving Voltage Problems in Low Voltage Grids: An Estonian Case Study," Energies, MDPI, vol. 15(3), pages 1-22, February.
    2. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    3. António Sérgio Faria & Tiago Soares & Tiago Sousa & Manuel A. Matos, 2020. "Participation of an EV Aggregator in the Reserve Market through Chance-Constrained Optimization," Energies, MDPI, vol. 13(16), pages 1-12, August.
    4. Sara Deilami & S. M. Muyeen, 2020. "An Insight into Practical Solutions for Electric Vehicle Charging in Smart Grid," Energies, MDPI, vol. 13(7), pages 1-13, March.
    5. Wanhao Yang & Hong Wang & Zhijie Wang & Xiaolin Fu & Pengchi Ma & Zhengchen Deng & Zihao Yang, 2020. "Optimization Strategy of Electric Vehicles Charging Path Based on “Traffic-Price-Distribution” Mode," Energies, MDPI, vol. 13(12), pages 1-26, June.

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