Title :
A hybrid algorithm for planning public charging stations
Author :
Bendiabdellah, Zoulikha ; Senouci, Sidi Mohammed ; Feham, Mohamed
Author_Institution :
STIC Lab., Abou Bekr Belkaid Univ., Tlemcen, Algeria
Abstract :
Green mobility solutions are receiving currently an enormous attention. Indeed, during last years, electric vehicles, being part of the field of the smart-grid, entered the automobile market of the whole world. This technology requires an effective deployment of charging stations of electric refill since the main problem in this system remains over the duration of refill of the batteries. In this work, we propose an optimized algorithm to locate electric charging stations. The main task of the algorithm is to find the best site of charging stations locations so as to minimize loss on the way to the charging station, as well as minimize investment cost, we take into account several constraints to find the optimal number and placement of charging station. Our hybrid algorithm with improved K-means clustering and genetic algorithm can be used to find optimal number and place of charging stations.
Keywords :
electric vehicles; genetic algorithms; pattern clustering; K-means clustering; electric charging stations locations; genetic algorithm; hybrid algorithm; investment cost minimization; optimized algorithm; public charging stations planning; Charging stations; Clustering algorithms; Genetic algorithms; Genetics; Investment; Mathematical model; Optimization; Smart-Grid; charging stations; electric vehicles; genetic optimization; k-means clustring;
Conference_Titel :
Global Information Infrastructure and Networking Symposium (GIIS), 2014
Conference_Location :
Montreal, QC
DOI :
10.1109/GIIS.2014.6934262