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Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms

Author

Listed:
  • Monica Alonso

    (Department of Electrical Engineering, University Carlos III of Madrid, Avda de la Universidad 30, Madrid 28911, Spain)

  • Hortensia Amaris

    (Department of Electrical Engineering, University Carlos III of Madrid, Avda de la Universidad 30, Madrid 28911, Spain)

  • Jean Gardy Germain

    (Gas Natural Fenosa, Avda. San Luis 77, Madrid 28033, Spain)

  • Juan Manuel Galan

    (Gas Natural Fenosa, Avda. San Luis 77, Madrid 28033, Spain)

Abstract

Transportation electrification has become an important issue in recent decades and the large scale deployment of electric vehicles (EVs) has yet to be achieved. The smart coordination of EV demand addresses an improvement in the flexibility of power systems and reduces the costs of power system investment. The uncertainty in EV drivers’ behaviour is one of the main problems to solve to obtain an optimal integration of EVs into power systems. In this paper, an optimisation algorithm to coordinate the charging of EVs has been developed and implemented using a Genetic Algorithm (GA), where thermal line limits, the load on transformers, voltage limits and parking availability patterns are taken into account to establish an optimal load pattern for EV charging-based reliability. This methodology has been applied to an existing residential low-voltage system. The results indicate that a smart charging schedule for EVs leads to a flattening of the load profile , peak load shaving and the prevention of the aging of power system elements.

Suggested Citation

  • Monica Alonso & Hortensia Amaris & Jean Gardy Germain & Juan Manuel Galan, 2014. "Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms," Energies, MDPI, vol. 7(4), pages 1-27, April.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:4:p:2449-2475:d:35240
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    References listed on IDEAS

    as
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