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Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load
Authors:Phillip Paevere  Andrew Higgins  Zhengen Ren  Mark Horn  George Grozev  Cheryl McNamara
Institution:1. CSIRO Ecosystem Sciences, P.O. Box 56, Highett, VIC, Australia
2. CSIRO Ecosystem Sciences, P.O. Box 2583, Brisbane, QLD, Australia
3. CSIRO Computational Informatics, North Ryde, NSW, Australia
Abstract:This paper presents a composite methodology for obtaining spatial and temporal projections of charging demand and peak-shaving potential from plug-in electric vehicles (EVs), and the associated spatio-temporal impacts on peak household electrical load. The methodology comprises a suite of models of future EV uptake, travel by households, household electricity demand and recharge/discharge of EVs at their home locations. The analysis is disaggregated to hourly time-steps over a full year, and spatially to mesh blocks comprising around 250 houses per block. The modelling suite is applied to an analysis of peak household load impacts across the state of Victoria, Australia, under nine different combinations of EV uptake and charging/discharging behaviour. The projected increase in peak household electrical loads under expected penetration rates and charging demands is less than 10 % on most high-demand days, but can be up to 15 % on a handful of days and geographic locations. Peak-load impacts under off-peak charging are mostly less than 5 %. With judicious EV discharging strategies, there is potential to shave peak loads on the highest demand days by up to 5 %.
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