Optimal Locating of Electric Vehicle Charging Stations by Application of Genetic Algorithm

被引：41

作者：

Akbari, Milad ^{[1
]}

Brenna, Morris ^{[1
]}

Longo, Michela ^{[1
]}

机构：

[1] Politecn Milan, Dept Energy, Via La Masa 34, I-20156 Milan, MI, Italy

来源：

SUSTAINABILITY | 2018年 / 10卷 / 04期

关键词：

electric vehicles; genetic algorithm; charging stations; bass model; smart cities;

D O I：

10.3390/su10041076

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The advent of alternative vehicle technologies such as Electrical Vehicles (EVs) is an efficient effort to reduce the emission of carbon oxides and nitrogen oxides. Ironically, EVs poses concerns related to vehicle recharging and management. Due to the significance of charging station infrastructure, electric vehicles' charging stations deployment is investigated in this work. Its aim is to consider several limitations such as the power of charging station, the average time needed for each recharge, and traveling distance per day. Initially, a mathematical formulation of the problem is framed. Then, this problem is optimized by application of Genetic Algorithm (GA), with the objective to calculate the necessary number of charging stations then finding the best positions to locate them to satisfy the clients demand.

引用

页数：14

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