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A Fuzzy Energy Management Strategy for the Coordination of Electric Vehicle Charging in Low Voltage Distribution Grids

Author

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  • Vasileios Boglou

    (Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, 671 00 Xanthi, Greece)

  • Christos-Spyridon Karavas

    (Department of Natural Resources Development and Agricultural Engineering, School of Environment and Agricultural Engineering, Agricultural University of Athens, 118 55 Athens, Greece
    Research, Technology & Development Department, Independent Power Transmission Operator (IPTO) S.A., 104 43 Athens, Greece)

  • Konstantinos Arvanitis

    (Department of Natural Resources Development and Agricultural Engineering, School of Environment and Agricultural Engineering, Agricultural University of Athens, 118 55 Athens, Greece)

  • Athanasios Karlis

    (Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, 671 00 Xanthi, Greece)

Abstract

Electric vehicles (EVs) have become widespread during the last decade because of the distinct advantages they offer compared to the conventional ones. However, the increased penetration of EVs in the global transportation market has led increased electricity demands, which is expected to affect the operation of energy distribution systems. In the present paper, a demonstration about the effects of uncontrolled EVs charging in a case study low voltage (LV) network is demonstrated and a fuzzy energy management strategy for the coordination of EV charging in LV networks is presented, by including the distance of the EVs from the transformers in the fuzzy management systems for the first time. The Institute of Electrical and Electronics Engineers (IEEE) European Test Feeder is used as a case study low voltage distribution grid. In particular, the developed system configuration takes into consideration the architecture of the grid, the ampacities of the lines and the voltages at the system’s buses. Moreover, electric vehicles are considered as agent-based models, which are characterized by the model of each EV, the state-of-charge of their batteries and the charging power. In particular, an investigation into the effects of uncontrolled charging is performed, in which two approaches are examined. The first approach investigates the maximum number of chargeable EVs in the case study network and how it is influenced by the grid’s household loads. The second approach examines the number of network undervoltages and lines ampacity violations in a set of simulation scenarios. The results of the first approach show that the distance of the EVs from the networks substation affects the maximum number of chargeable EVs in a significant manner. Based on the observed results of the two approaches, a fuzzy management system is designed for the coordination of EV changing, which takes into account the distance from the EV charging points to the feeder substation, the state-of-charge of the EVs’ batteries and the EVs’ charging delay time.

Suggested Citation

  • Vasileios Boglou & Christos-Spyridon Karavas & Konstantinos Arvanitis & Athanasios Karlis, 2020. "A Fuzzy Energy Management Strategy for the Coordination of Electric Vehicle Charging in Low Voltage Distribution Grids," Energies, MDPI, vol. 13(14), pages 1-34, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3709-:d:386549
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    References listed on IDEAS

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    1. Fuad Un-Noor & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Mohammad Nurunnabi Mollah & Eklas Hossain, 2017. "A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development," Energies, MDPI, vol. 10(8), pages 1-84, August.
    2. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    3. Chong Cao & Luting Wang & Bo Chen, 2016. "Mitigation of the Impact of High Plug-in Electric Vehicle Penetration on Residential Distribution Grid Using Smart Charging Strategies," Energies, MDPI, vol. 9(12), pages 1-19, December.
    4. Hu, Junjie & Morais, Hugo & Sousa, Tiago & Lind, Morten, 2016. "Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1207-1226.
    5. Christos-Spyridon Karavas & Konstantinos Arvanitis & George Papadakis, 2017. "A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids," Energies, MDPI, vol. 10(11), pages 1-22, November.
    6. Gaizka Saldaña & Jose Ignacio San Martin & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Electric Vehicle into the Grid: Charging Methodologies Aimed at Providing Ancillary Services Considering Battery Degradation," Energies, MDPI, vol. 12(12), pages 1-37, June.
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    11. 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.
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