Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

Jorge García Álvarez, Miguel Ángel González, Camino Rodríguez Vela and Ramiro Varela
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Jorge García Álvarez: Department of Computer Science, University of Oviedo, 33204 Gijón, Spain
Miguel Ángel González: Department of Computer Science, University of Oviedo, 33204 Gijón, Spain
Camino Rodríguez Vela: Department of Computer Science, University of Oviedo, 33204 Gijón, Spain
Ramiro Varela: Department of Computer Science, University of Oviedo, 33204 Gijón, Spain

Energies, 2018, vol. 11, issue 10, 1-19

Abstract: Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.

Keywords: electric vehicle charging; scheduling; artificial bee colony; local search; metaheuristics (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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