A key enabler for Electric Vehicles (EVs) is destination charging – allowing users to charge their vehicles while parked at amenities such as supermarkets, gyms, cinemas and shopping centres – leaving their vehicles for periods ranging from 10 minutes to 3 hours. This paper presents a Monte Carlo (MC)-based method for the characterization of likely demand profiles of EV destination charging at these locations based on smartphone users’ anonymised positional data captured in the Google Maps Popular Times feature. Unlike the majority of academic works on the subject, which tend to rely on users’ responses to surveys, these data represent individuals’ actual movements rather than how they might recall or divulge them. Through a smart charging approach proposed in this paper, likely electrical demand profiles for EV destination charging at different amenities are presented. The method is demonstrated by way of two case studies. Firstly, it is applied to a large GB shopping centre to show how the approach can be used to derive suitable specifications for large charging infrastructure to maximise revenue or EV service provision. Secondly, it is applied to a GB supermarket in a residential area to show how the approach can be used to examine network impact for a distribution-connected destination charging facility.
|Number of pages||8|
|Publication status||Published - 15 Oct 2018|
|Event||E-Mobility Power System Integration Symposium 2018 - KTH, Stockholm, Sweden|
Duration: 15 Oct 2018 → 15 Oct 2018
|Conference||E-Mobility Power System Integration Symposium 2018|
|Period||15/10/18 → 15/10/18|
- electric vehicles
- destination charging
- Monte Carlo
Dixon, J., Bell, K., & Elders, I. (2018). Electric vehicle destination charging characterisations at popular amenities. Paper presented at E-Mobility Power System Integration Symposium 2018, Stockholm, Sweden.