@article{ref1,
title="A novel spatial-temporal model for charging plug hybrid electrical vehicles based on traffic-flow analysis and Monte Carlo method",
journal="ISA transactions",
year="2020",
author="Abedini, Mohamad and Mohammadi, Mohammad Reza and Afshar, Mostafa",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="The increase of using electric vehicles (EVs) may increase power demand and therefore major effects on the power system. Therefore, if we do not have an  appropriate program for utilizing and managing battery charging in the EVs, the  charging process may coincide with the peak of power consumption and cause severe  network problems. This paper deals with modeling the problem and estimating load  consumption in EVs connected to the system. The EVs have been considered based on a  random load and a probabilistic process. To manage the EVs, a traffic method called  the spatial-temporal scheme, which uses the Monte Carlo algorithm, has been  proposed. Also, the proposed method can be used to represent a model of electric  vehicles changes in their battery charge and their need for charging at different  times of a full day in different zones of the city. The proposed method has been  simulated in the Matlab software and implemented for Hamedan province. The results  show that using this method of estimation can improve the management of EVs.<p /> <p>Language: en</p>",
language="en",
issn="0019-0578",
doi="10.1016/j.isatra.2020.12.051",
url="http://dx.doi.org/10.1016/j.isatra.2020.12.051"
}