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

Monica Alonso, Hortensia Amaris, Jean Gardy Germain and Juan Manuel Galan
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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

Energies, 2014, vol. 7, issue 4, 1-27

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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (39)

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