Multivariate Dependence Modeling of Electric Vehicle Charging Stochastic Parameters

Electric vehicles are considered a sustainable mode of terrestrial transport worldwide because of low- or zero-carbon emissions. Public charging stations, particularly fast and extra fast, play a crucial role in adopting and developing electric vehicles. To enable optimum planning of the fast charging stations, multivariate dependence of electric vehicle charging variables regarding stochastic nature should be taken into account. This paper uses multiple Elliptical and Archimedean copula functions to model the correlation/dependency between the electric vehicle charging characteristic parameters. Typically, by employing the multivariate copulas, synthetic electric vehicle charging data or observations are effectively generated for accurate simulation of multiple theoretical and practical applications, such as planning electric vehicle charging infrastructures while handling inherent variability and complex dependencies of electric vehicle charging characteristic parameters. Simulations are carried out in R.