Mendeley
TY  _  JOUR
ID  -  13980318189986
TI  -  Probabilistic Modeling of Fast Charging Station Load Demand for Public Electric Vehicles
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Yousefi Hossein
AU  -  Tourandaz Kenari Meghdad
AU  -  Sepasian Mohammad Sadegh
AD  -  دانشگاه شهید بهشتی
AD  -  دانشگاه شهید بهشتی
AD  -  دانشگاه شهید بهشتی
Y1  -  2019
PY  -  2019
VL  -  1
IS  -  
SP  -  42
EP  -  50
KW  -  Charging loadelectric vehiclesfast charging stationMonte Carlo simulationprobabilistic modelingqueueing theory
DO  -  
N2  -  Considering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention to the impacts of PEVs charging on the network. In this paper, a probabilistic model based on the queueing theory is extracted using Monte Carlo simulation for modeling EV charging station load. It is assumed that the vehicles are the taxis of Amol city in Mazandaran province. Required data such as the time of arrival and the state of charge of the battery before charging, were collected and extracted using three methods from intra-city taxis in the city of Amol. To obtain the demand load of EV charging, the traffic-based behavior of drivers is needed. This behavior is stochastic. Therefore, its related variables will not be deterministic and must be evaluated using probabilistic methods.
UR  - rimag.ir/en/Article/28501
L1  - rimag.ir/en/Article/Download/28501
ER  -  
