An Analysis of the Charging Characteristics of Electric Vehicles Based on Measured Data and Its Application

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Abstract
The accurate modelling of the charging characteristics of electric vehicles (EVs) is the basis for the load forecasting, infrastructure planning, and orderly charging management. While, research based on the measured charging data of EVs is seldom carried out, and the concrete modelling of the correlations of various parameters is a gap in the knowledge. Aiming at this, we carried out an investigation based on operational data, from August 2016 to August 2017, of an EV charging service company in Nanjing, China. The time-energy characteristics of EV charging behaviour can be described using the probability distributions and correlations of three charging parameters, i.e. charging start time, charging duration, and charged capacity. In the research, we fitted the probability densities of these charging parameters using the kernel estimation method and verified the correlations of time parameters of the charging behaviour. Multiple copula functions were used to model the correlation between the time and energy parameters of different types of charging behaviours. On this basis, we also carried out stochastic simulation for the load curve of disordered charging and analysed the potential of the EV charging load participating in the orderly management and its coordination with the output of power generation using renewable energy.
Funding Information
  • Major State Research Development Program of China (2016YFB0101800)

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