1 Khoo, Y.B., Wang, C-H., Paevere, P. and Higgins, A. (2014). “Statistical modelling of electric vehicle electricity consumption in the Victorian EV trial, Australia.” Transportation Research Part D: Transport and Environment, Vol. 32, 263–277, October. DOI: 10.1016/j.trd.2014.08.017. Statistical modeling of Electric V ehicle electricity consumption in the Victorian EV Trial , Australia Yong Bing Khoo a , Chi-Hsiang Wang a , Phillip Paevere a , Andrew Higgins b a CSIRO Ecosystem Sciences and CSIRO Energy Transformed Flagship, 37 Graham Road, Highett, Victoria 3190, Australia b CSIRO Ecosystem Sciences and CSIRO Energy Transformed Flagship, 41 Boggo Road, Dutton Park, Queensland 4102, Australia yongbing.khoo@csiro.au, chi-hsiang.wang@csiro.au, phillip.paevere@csiro.au, andrew.higgins@csiro.au Corresponding author: Yong Bing Khoo (Tel: +61 3 9252 6051) ABSTRACT The market share of Electric Vehicles (EVs), an attractive alternative to conventional vehicles, is expected to exceed 30% of all vehicles by 2033 in Australia. Although the expected EV uptake may place greater burdens on electricity networks, the potential impacts contributed by different EV user categories and vehicle models to peak loads at different times during the day are not well understood. This paper addresses the issue through statistical analysis of the charge events in the Victorian EV Trial in Australia as well as modeling the charging behaviors according to participant categories and vehicle models. The analysis was performed on 4,933 charge events that were recorded by both private and public Electric Vehicle Supply Equipment. In total, these events consumed over 33MWh of energy over 12,170h by the 178 trial participants, out of which about 70% were household participants while the others were fleet participants. Based on a range of EV uptake scenarios and modeled charging behaviors from the trial, the power demand in the summer of 2032/ 33 was estimated for all of Victoria. The results of the simulations show that the broad scale uptake of EVs produces a relatively small increase in overall power demand (estimated to be between 5.72% and 9.79% in 2032/ 33).