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EV Smart-Charging Strategy for Power Management in Distribution Grid with High Penetration of Distributed Generation

Author

Listed:
  • Geraldo L. Maia

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Caio C. L. Santos

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Paulo R. M. Nunes

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • José F. C. Castro

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Davidson C. Marques

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Luiz H. A. De Medeiros

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Leonardo R. Limongi

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Márcio E. C. Brito

    (Electrical Engineering Department-DEE, Federal University of Pernambuco–UFPE, Recife 50670-901, PE, Brazil)

  • Nicolau K. L. Dantas

    (Institute of Technology Edson Mororó Moura (ITEMM), Recife 51020-280, PE, Brazil)

  • Antônio V. M. L. Filho

    (Institute of Technology Edson Mororó Moura (ITEMM), Recife 51020-280, PE, Brazil)

  • Amanda L. Fernandes

    (Innovation Department, CPFL Energia, Campinas 13088-900, SP, Brazil)

  • Jiyong Chai

    (Innovation Department, CPFL Energia, Campinas 13088-900, SP, Brazil)

  • Chenxin Zhang

    (Innovation Department, CPFL Energia, Campinas 13088-900, SP, Brazil)

Abstract

Accelerated environmental impacts are a growing concern in the modern world. Electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. In this context, this work presents a framework for controlling an electric vehicle (EV)-charging station integrated into a microgrid application as a basis for creating the infrastructure integrated into a smart grid concept. Considering the electrification of the transportation sector future perspectives, a brief review is conducted on the impacts of EV fleet growth in different countries and how smart-charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV-charging stations. An analysis of the technical characteristics and the tools that enable the deployment of a fleet-charging operator are examined, specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. A new EV-charging station control method is proposed to manage the impacts of distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, an integration architecture via IEC 61850 for these elements is proposed, in a practical implementation for variable power control, considering different strategies to deal with distributed generation impact using EV-fleet-charging power demand dynamic management.

Suggested Citation

  • Geraldo L. Maia & Caio C. L. Santos & Paulo R. M. Nunes & José F. C. Castro & Davidson C. Marques & Luiz H. A. De Medeiros & Leonardo R. Limongi & Márcio E. C. Brito & Nicolau K. L. Dantas & Antônio V, 2024. "EV Smart-Charging Strategy for Power Management in Distribution Grid with High Penetration of Distributed Generation," Energies, MDPI, vol. 17(21), pages 1-27, October.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:21:p:5394-:d:1509719
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    References listed on IDEAS

    as
    1. Meinrenken, Christoph J. & Lackner, Klaus S., 2015. "Fleet view of electrified transportation reveals smaller potential to reduce GHG emissions," Applied Energy, Elsevier, vol. 138(C), pages 393-403.
    2. Glyniadakis, Sofia & Balestieri, José Antônio Perrella, 2023. "Brazilian light vehicle fleet decarbonization scenarios for 2050," Energy Policy, Elsevier, vol. 181(C).
    3. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    4. Fernando A. Assis & Francisco C. R. Coelho & José Filho C. Castro & Antonio R. Donadon & Ronaldo A. Roncolatto & Pedro A. C. Rosas & Vittoria E. M. S. Andrade & Rafael G. Bento & Luiz C. P. Silva & Jo, 2024. "Assessment of Regulatory and Market Challenges in the Economic Feasibility of a Nanogrid: A Brazilian Case," Energies, MDPI, vol. 17(2), pages 1-18, January.
    5. José F. C. Castro & Ronaldo A. Roncolatto & Antonio R. Donadon & Vittoria E. M. S. Andrade & Pedro Rosas & Rafael G. Bento & José G. Matos & Fernando A. Assis & Francisco C. R. Coelho & Rodolfo Quadro, 2023. "Microgrid Applications and Technical Challenges—The Brazilian Status of Connection Standards and Operational Procedures," Energies, MDPI, vol. 16(6), pages 1-25, March.
    6. Yandi G. Landera & Oscar C. Zevallos & Rafael C. Neto & Jose F. da Costa Castro & Francisco A. S. Neves, 2023. "A Review of Grid Connection Requirements for Photovoltaic Power Plants," Energies, MDPI, vol. 16(5), pages 1-24, February.
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