Spatial optimal location of EV charging stations based on K-means clustering method

Author(s):  
Qingsheng Shi ◽  
Yi Cao ◽  
Fuqiang Huo
2021 ◽  
Vol 199 ◽  
pp. 107391
Author(s):  
Leonardo Bitencourt ◽  
Tiago P. Abud ◽  
Bruno H. Dias ◽  
Bruno S.M.C. Borba ◽  
Renan S. Maciel ◽  
...  

2021 ◽  
Vol 19 ◽  
pp. 33-38
Author(s):  
Vishnu Suresh ◽  
◽  
Przemyslaw Janik ◽  
Dominika Kaczorowska

This paper presents an analytical approach to finding an optimal location for an EV charging station based on energy savings in a local microgrid. The analysis is carried out on days obtained by clustering yearly load data and by running an energy management system that runs on MATLAB interior point method. The microgrid is composed of both renewable and non-renewable energy sources. The charging station is equipped with a controlled charging feature and this study considers 2 EV charging strategies out of which the one benefitting the power system is adopted.


2014 ◽  
Vol 556-562 ◽  
pp. 3972-3975 ◽  
Author(s):  
Qing Sheng Shi ◽  
Xiao Zhen Zheng

As plug-in hybrid electric vehicles and battery electric vehicle ownership is expanding, there is a growing need for widely distributed publicly accessible charging stations. Building a charging station cost too much. Therefore, optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the optimal location of charging stations using fuzzy C-means clustering method. Preliminary of fuzzy C-means clustering method is introduced first followed by the procedure of charging station optimal location using Fuzzy C-means Clustering. Finally, simulation results show the validity of proposed method.


2013 ◽  
Vol 380-384 ◽  
pp. 3400-3403 ◽  
Author(s):  
Qing Sheng Shi ◽  
Yi Cao

Building enough charging stations is the only way to let new energy vehicles come into our daily life. While, the cost of building a charging station is very expensive. Therefore, spatial optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the spatial optimal location of charging stations using Gaussian Mixture Model clustering and charging requirement spots are taken as the clustering benchmark. The clustering procedure of charging station spatial optimal location is programmed using m-language. Finally, simulation results show the validity of proposed method.


Author(s):  
Hossein Parastvand ◽  
Octavian Bass ◽  
Mohammad A. S. Masoum ◽  
Zeinab Moghaddam ◽  
Stefan Lachowicz ◽  
...  

2021 ◽  
Vol 2 (2) ◽  
pp. 1-21
Author(s):  
Hossam ElHussini ◽  
Chadi Assi ◽  
Bassam Moussa ◽  
Ribal Atallah ◽  
Ali Ghrayeb

With the growing market of Electric Vehicles (EV), the procurement of their charging infrastructure plays a crucial role in their adoption. Within the revolution of Internet of Things, the EV charging infrastructure is getting on board with the introduction of smart Electric Vehicle Charging Stations (EVCS), a myriad set of communication protocols, and different entities. We provide in this article an overview of this infrastructure detailing the participating entities and the communication protocols. Further, we contextualize the current deployment of EVCSs through the use of available public data. In the light of such a survey, we identify two key concerns, the lack of standardization and multiple points of failures, which renders the current deployment of EV charging infrastructure vulnerable to an array of different attacks. Moreover, we propose a novel attack scenario that exploits the unique characteristics of the EVCSs and their protocol (such as high power wattage and support for reverse power flow) to cause disturbances to the power grid. We investigate three different attack variations; sudden surge in power demand, sudden surge in power supply, and a switching attack. To support our claims, we showcase using a real-world example how an adversary can compromise an EVCS and create a traffic bottleneck by tampering with the charging schedules of EVs. Further, we perform a simulation-based study of the impact of our proposed attack variations on the WSCC 9 bus system. Our simulations show that an adversary can cause devastating effects on the power grid, which might result in blackout and cascading failure by comprising a small number of EVCSs.


2021 ◽  
Author(s):  
T. Muthamizhan ◽  
M.Jagadeesh Kumar ◽  
P. Rathnavel ◽  
Md. Aijaz ◽  
A. Sivakumar

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