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Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling

Author

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  • Asaad Mohammad

    (Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand)

  • Ramon Zamora

    (Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand)

  • Tek Tjing Lie

    (Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland 1010, New Zealand)

Abstract

Electric vehicles (EVs) are one of a prominent solution for the sustainability issues needing dire attention like global warming, depleting fossil fuel reserves, and greenhouse gas (GHG) emissions. Conversely, EVs are shown to emit higher emissions (measured from source to tailpipe) for the fossil fuel-based countries, which necessitates renewable energy sources (RES) for maximizing EV benefits. EVs can also act as a storage system, to mitigate the challenges associated with RES and to provide the grid with ancillary services, such as voltage regulation, frequency regulation, spinning reserve, etc. For extracting maximum benefits from EVs and minimizing the associated impact on the distribution network, modelling optimal integration of EVs in the network is required. This paper focuses on reviewing the state-of-the-art literature on the modelling of grid-connected EV-PV (photovoltaics) system. Further, the paper evaluates the uncertainty modelling methods associated with various parameters related to the grid-connected EV-PV system. Finally, the review is concluded with a summary of potential research directions in this area. The paper presents an evaluation of different modelling components of grid-connected EV-PV system to facilitate readers in modelling such system for researching EV-PV integration in the distribution network.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4541-:d:407570
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    21. Aragón, Gustavo & Pandian, Vinoth & Krauß, Veronika & Werner-Kytölä, Otilia & Thybo, Gitte & Pautasso, Elisa, 2022. "Feasibility and economical analysis of energy storage systems as enabler of higher renewable energy sources penetration in an existing grid," Energy, Elsevier, vol. 251(C).

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