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Planning and Operation of Plug-In Electric Vehicles pp 23–47Cite as

Studying the Effects of Optimal Fleet Management of Plug-In Electric Vehicles on the Unit Commitment Problem Considering the Technical and Social Aspects

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Abstract

In this chapter, the effects of fleet management (FM) of plug-in electric vehicles (PEVs) on the generation scheduling and unit commitment (UC) problem of a generation system are studied considering the technical and social aspects of the problem. The objective function of generation company (GENCO) is to minimize the operation cost of generation system by the optimal FM of PEVs considering low, moderate, and high PEV penetration levels. Herein, the drivers are categorized in three different social classes based on their income level including low-income, moderate-income, and high-income. In this study, the behavior of each social class of drivers is modelled based on the reaction of drivers with respect to the value of incentive, suggested by the GENCO, to transfer their charging demand from the peak period to the off-peak one. A sensitivity analysis is performed for the total cost of problem with respect to value of incentive considering different PEV penetration levels and various social classes of drivers. Moreover, the value of error (due to the unrealistic modelling of drivers’ social class) in the optimal value of incentive, minimum total cost of problem, and generation scheduling and commitment of generation units is investigated.

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Authors and Affiliations

  1. Department of Physics and Astronomy, University of Alabama in Huntsville, Huntsville, AL, USA

    Mehdi Rahmani-Andebili

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  1. Mehdi Rahmani-Andebili
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Rahmani-Andebili, M. (2019). Studying the Effects of Optimal Fleet Management of Plug-In Electric Vehicles on the Unit Commitment Problem Considering the Technical and Social Aspects. In: Planning and Operation of Plug-In Electric Vehicles. Springer, Cham. https://doi.org/10.1007/978-3-030-18022-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-18022-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18021-8

  • Online ISBN: 978-3-030-18022-5

  • eBook Packages: EnergyEnergy (R0)

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