GENETIC ALGORITHM FOR OPTIMAL LOCATION OF ELECTRIC VEHICLE CHARGE STATION

Cheng Wang; Jian Wei Li; Peng He; Weiping Cui; Xin Da Li

doi:10.46855/energy-proceedings-1485

GENETIC ALGORITHM FOR OPTIMAL LOCATION OF ELECTRIC VEHICLE CHARGE STATION

Cheng Wang, Jian Wei Li, Peng He, Weiping Cui, Xin Da Li

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

Abstract

With increasing number of Electric Vehicles(EVs),more attention is being paid to EV’s charge stations. These stations play an essential role in EV industry chain.Choosing the optimal locations for these stations is becoming vitally important. Not only for power loss reduction,but also for power system security. In this paper a novel optimal charge station location method is informed based on active and reactive power flow analysis by using Genetic Algorithm (GA) in terms of power loss minimization.Results for the36-bus Distribution Network (DN) are presented.It is demonstrated that installing three stations in optimal locations in the tested network, power loss reduces by 0.088 MW, compared with the situation with two stations.

Original language	English
Journal	Energy Proceedings
Volume	2
DOIs	https://doi.org/10.46855/energy-proceedings-1485
Publication status	Published - 2019
Event	11th International Conference on Applied Energy, ICAE 2019 - Västerås, Sweden Duration: 12 Aug 2019 → 15 Aug 2019

Keywords

active and reactive power flow analysis
charge stations’location
EVs
GA optimisation
power loss reduction

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.46855/energy-proceedings-1485

Cite this

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title = "GENETIC ALGORITHM FOR OPTIMAL LOCATION OF ELECTRIC VEHICLE CHARGE STATION",

abstract = "With increasing number of Electric Vehicles(EVs),more attention is being paid to EV{\textquoteright}s charge stations. These stations play an essential role in EV industry chain.Choosing the optimal locations for these stations is becoming vitally important. Not only for power loss reduction,but also for power system security. In this paper a novel optimal charge station location method is informed based on active and reactive power flow analysis by using Genetic Algorithm (GA) in terms of power loss minimization.Results for the36-bus Distribution Network (DN) are presented.It is demonstrated that installing three stations in optimal locations in the tested network, power loss reduces by 0.088 MW, compared with the situation with two stations.",

keywords = "active and reactive power flow analysis, charge stations{\textquoteright}location, EVs, GA optimisation, power loss reduction",

author = "Cheng Wang and Li, {Jian Wei} and Peng He and Weiping Cui and Li, {Xin Da}",

note = "Publisher Copyright: {\textcopyright} 2019 ICAE.; 11th International Conference on Applied Energy, ICAE 2019 ; Conference date: 12-08-2019 Through 15-08-2019",

year = "2019",

doi = "10.46855/energy-proceedings-1485",

language = "English",

volume = "2",

journal = "Energy Proceedings",

issn = "2004-2965",

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T1 - GENETIC ALGORITHM FOR OPTIMAL LOCATION OF ELECTRIC VEHICLE CHARGE STATION

AU - Wang, Cheng

AU - Li, Jian Wei

AU - He, Peng

AU - Cui, Weiping

AU - Li, Xin Da

PY - 2019

Y1 - 2019

N2 - With increasing number of Electric Vehicles(EVs),more attention is being paid to EV’s charge stations. These stations play an essential role in EV industry chain.Choosing the optimal locations for these stations is becoming vitally important. Not only for power loss reduction,but also for power system security. In this paper a novel optimal charge station location method is informed based on active and reactive power flow analysis by using Genetic Algorithm (GA) in terms of power loss minimization.Results for the36-bus Distribution Network (DN) are presented.It is demonstrated that installing three stations in optimal locations in the tested network, power loss reduces by 0.088 MW, compared with the situation with two stations.

AB - With increasing number of Electric Vehicles(EVs),more attention is being paid to EV’s charge stations. These stations play an essential role in EV industry chain.Choosing the optimal locations for these stations is becoming vitally important. Not only for power loss reduction,but also for power system security. In this paper a novel optimal charge station location method is informed based on active and reactive power flow analysis by using Genetic Algorithm (GA) in terms of power loss minimization.Results for the36-bus Distribution Network (DN) are presented.It is demonstrated that installing three stations in optimal locations in the tested network, power loss reduces by 0.088 MW, compared with the situation with two stations.

KW - active and reactive power flow analysis

KW - charge stations’location

KW - EVs

KW - GA optimisation

KW - power loss reduction

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DO - 10.46855/energy-proceedings-1485

M3 - Conference article

AN - SCOPUS:85202593034

SN - 2004-2965

VL - 2

JO - Energy Proceedings

JF - Energy Proceedings

T2 - 11th International Conference on Applied Energy, ICAE 2019

Y2 - 12 August 2019 through 15 August 2019

ER -

GENETIC ALGORITHM FOR OPTIMAL LOCATION OF ELECTRIC VEHICLE CHARGE STATION

Abstract

Keywords

UN SDGs

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