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 statis-tical 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 sto-chastic, realistic and detailed EV profiles to carry out impact and/or Smart Grid-related studies. Finally, the effects of the EV demand on future UK distribution networks are discussed.
|Title of host publication||IEEE/PES Innovative Smart Grid Technologies ISGT Latin America 2015|
|Number of pages||6|
|Publication status||Published - Oct 2015|
|Event||IEEE/PES Innovative Smart Grid Technologies ISGT Latin America 2015 - |
Duration: 5 Oct 2015 → 7 Oct 2015
|Conference||IEEE/PES Innovative Smart Grid Technologies ISGT Latin America 2015|
|Period||5/10/15 → 7/10/15|