This paper offers a comprehensive and exact model for Plug-in Hybrid Electric Vehicle (PHEV) aggregation based on the real statistics. For this purpose, available transportation and technical reports are analyzed to extract Cumulative Distribution Functions and accurate modeling of PHEVs charging load profile. We can study PHEVs effects on the distribution system by analyzing available registered data; however, the main problem is that such data, due to the low penetration of PHEVs, are not accessible, and expensive monitoring equipment such as Global Positioning Systems are needed to collect such data. Therefore, due to the lack of access to such data, researchers have offered different estimations for the charging load profile of PHEVs using statistical methods. In this study, a new model for the initial state of charge (SOC) is introduced that it is a function of fuel consumption of the vehicles. The driving behaviors such as speed and road slope have been considered in the proposed model. Simulation results show the impressiveness effectiveness and accuracy of the proposed methodology.
A New Model of Charging Demand Related to Plug-in Hybrid Electric Vehicles Aggregation
2017
Article (Journal)
English
Transportation , Electric charge , Hybrid vehicles , load profile , Trucks , Stress concentration , charge level , Computer simulation , Agglomeration , Electric vehicles , Driving , aggregated model , Plug-in hybrid electric vehicles (PHEVs) , Penetration , Electric hybrid vehicles , charging curve , Satellite navigation systems , all electric range (AER) , Statistical methods , Fuel consumption , Monte Carlo simulation , distribution system , state of charge (SOC) , Accessibility , power unbalance , Charging , Fuels , Accuracy , Modelling , Distribution functions
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