Active THD reduction strategy for grid connected EV charging stations

Author(s):  
Mohamed Badawy ◽  
Adeeb Ahmed ◽  
Yilmaz Sozer ◽  
Ping Yi
Author(s):  
Hossein Parastvand ◽  
Octavian Bass ◽  
Mohammad A. S. Masoum ◽  
Zeinab Moghaddam ◽  
Stefan Lachowicz ◽  
...  

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 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

2021 ◽  
Author(s):  
Michele Barbieri ◽  
Massimo Ceraolo ◽  
Giovanni Lutzemberger ◽  
Davide Poli

Author(s):  
K. Liu ◽  
X.H. Sun

Electric vehicles (EVs) will certainly play an important role in addressing the energy and environmental challenges at current situation. However, location problem of EV charging stations was realized as one of the key issues of EVs launching strategy. While for the case of locating EV charging stations, more influence factors and constraints need to be considered since the EVs have some special attributes. The minimum requested charging time for EVs is usually more than 30minutes, therefore the possible delay time due to waiting or looking for an available station is one of the most important influence factors. In addition, the intention to purchase and use of EVs that also affects the location of EV charging stations is distributed unevenly among regions and should be considered when modelling. Unfortunately, these kinds of time-spatial constraints were always ignored in previous models. Based on the related research of refuelling behaviours and refuelling demands, this paper developed a new concept with dual objectives of minimum waiting time and maximum service accessibility for locating EV charging stations,named as Time-Spatial Location Model (TSLM). The proposed model and the traditional flow-capturing location model are applied on an example network respectively and the results are compared. Results demonstrate that time constraint has great effects on the location of EV charging stations. The proposed model has some obvious advantages and will help energy providers to make a viable plan for the network of EV charging stations.


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