Charging of plug-in electric vehicles: Stochastic modelling of load demand within domestic grids

Charging of plug-in electric vehicles: Stochastic modelling of load demand within domestic grids

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Publishing year : 2012

Conference : 20th Iranian Conference on Electrical Engineering

Number of pages : 5

Abstract: This paper proposes a stochastic approach based on Monte Carlo simulation to derive the load demand of a fleet of domestic commuter plug-in electric vehicles. At first, appropriatenon-Gaussian probability density functions are fitted to the employed data sets to generate random samples required in the Monte Carlo simulation. The datasets include home-based arrival times, daily travel distances and home-based departure times for randomly selected private ICE vehicles. In each iteration, the extraction of the charging profile is carried out for the individual PEVs in order to derive the fleet's hourly aggregated load profile. Then, the estimated probability density of the aggregate load of PEVs in each hour is estimated. Eventually, the expected value of the hourly load demand can be calculated for the achieved power distributions. The PEVs are assumed to be distributed through a distribution transformer. Thus, the profile of power delivered through the transformer to PEVs is achieved, which can be useful for various distribution systems applications such asnetwork planning, load management and probabilistic load flow, as well as sitting and size issues