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Energies 2014, 7(4), 2449-2475; doi:10.3390/en7042449

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

1
Department of Electrical Engineering, University Carlos III of Madrid, Avda de la Universidad 30, Madrid 28911, Spain
2
Gas Natural Fenosa, Avda. San Luis 77, Madrid 28033, Spain
*
Author to whom correspondence should be addressed.
Received: 30 January 2014 / Revised: 10 April 2014 / Accepted: 14 April 2014 / Published: 17 April 2014
(This article belongs to the Special Issue Advances in Hybrid Vehicles)

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.
Keywords: electric vehicles; smart grids; genetic algorithms electric vehicles; smart grids; genetic algorithms
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Alonso, M.; Amaris, H.; Germain, J.G.; Galan, J.M. Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms. Energies 2014, 7, 2449-2475.

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