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Research Article

Allocation of charging stations in Kota city using data analysis/machine learning

, , ORCID Icon &
Article: 2360437 | Published online: 03 Jun 2024
 

ABSTRACT

This paper proposes the allocation of charging stations of optimal capacity at appropriate locations within Kota city in Rajasthan state of India. The location of charging stations has been identified by considering various parameters including population density, family income, distribution network performance, number of electric vehicles and transformer capacity. The proposed approach of allocation of charging stations has been modeled mathematically and also by machine learning algorithms such as data mining, clustering with all the possible scenarios and constraints. In identifying suitable places for positioning charging stations in the city by observing different parameters and aspects, i.e. geo-statistical approaches, minimum traveling time and travel distance for charging stations has been included in the proposed approach. The proposed approach has been tested in MATLAB/Simulink environment.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Nomenclature

EV=

Electric Vehicles

CS=

Charging Station

EVCS=

Electric Vehicles Charging Station

PM10=

Particulate Matter

Dp=

density of population

N=

total population as a number of people

A=

the land area covered by that population

kn=

for a certain period of time the total number of vehicles per charge

PD=

power distribution function

C=

total charging capacity of the charging station

δ=

arrival rate

μ=

service rate of one server

Pi(),Ui()=

flow from bus-I into the system in terms of voltage magnitudes and angles

Pni,Pci=

generations at the bus

UniUci=

Demand at the bus

fln=

function define for real variable

fln=

function’s derivative for real variable

n=

number of iterations

ln=

root at value nth iteration.

Ri=

real power for any bus i

Vmi=

voltage magnitude

ei=

real components of the bus voltage vi

fi=

imaginary components of the bus voltage vi

Aik=

conductance

Dik=

susceptance

fTr=

Transformer’s

fPc=

power analysis

fAr=

various locality Area

fPd=

population density

fEc=

electricity consumption

fnv=

Vehicle counts

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