Conference Proceedings

A statistical analysis of EV charging behavior in the UK

J Quirós-Tortós, LF Ochoa, B Lees

2015 IEEE Pes Innovative Smart Grid Technologies Latin America Isgt Latam 2015 | IEEE | Published : 2016

Abstract

To truly quantify the impact of electric vehicles (EVs) on the electricity network and their potential interactions in the context of Smart Grids, it is crucial to understand their charging behavior. However, as EVs are yet to be widely adopted, these data are scarce. This work presents results of a thorough statistical analysis of the charging behavior of 221 real residential EV users (Nissan LEAF, i.e., 24kWh, 3.6 kW) spread across the UK and monitored over one year (68,000+ samples). Probability distribution functions (PDFs) of different charging features (e.g., start charging time) are produced for both weekdays and week-ends. Crucially, these unique PDFs can be used to create stochastic..

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University of Melbourne Researchers

Grants

Funding Acknowledgements

This work has been funded by EA Technology Limited, UK, through the Ofgem's Low Carbon Networks Fund Tier 2 Project "My Electric Avenue", 2013-2015.