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A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles

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  • Anna Auza

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal
    Faculty of Economics, University of Coimbra, Av. Dr. Dias da Silva 165, 3004-512 Coimbra, Portugal)

  • Ehsan Asadi

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Behrang Chenari

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

  • Manuel Gameiro da Silva

    (Associação para o Desenvolvimento da Aerodinâmica Industrial—ADAI, Department of Mechanical Engineering, University of Coimbra, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal)

Abstract

This paper systematically reviews the techniques and dynamics to study uncertainty modelling in the electric grids considering electric vehicles with vehicle-to-grid integration. Uncertainty types and the most frequent uncertainty modelling approaches for electric vehicles are outlined. The modelling approaches discussed in this paper are Monte Carlo, probabilistic scenarios, stochastic, point estimate method and robust optimisation. Then, Scopus is used to search for articles, and according to these categories, data from articles are extracted. The findings suggest that the probabilistic techniques are the most widely applied, with Monte Carlo and scenario analysis leading. In particular, 19% of the cases benefit from Monte Carlo, 15% from scenario analysis, and 10% each from robust optimisation and the stochastic approach, respectively. Early articles consider robust optimisation relatively more frequent, possibly due to the lack of historical data, while more recent articles adopt the Monte Carlo simulation approach. The uncertainty handling techniques depend on the uncertainty type and human resource availability in aggregate but are unrelated to the generation type. Finally, future directions are given.

Suggested Citation

  • Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4983-:d:1180612
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    References listed on IDEAS

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