Coincidence Factors for Domestic EV Charging from Driving and Plug-in Behavior

This study models the coincidence factor (CF) of EV charging given driving and plug-in behaviors by combining data sources from travel surveys and recorded EV charging data. From these we generate travel and plug-in behaviors by using a Monte Carlo approach to derive coincidence factors. By varying EV battery size, rated charging power and plug-in behavior, their influence on the coincidence factor is examined. The key results show that the coincidence factor decreases to less than 25% when considering more than 50 EVs with a charging level of 11 kW, with the coincidence factor strongly depending on the number of EVs considered. By contrast, driving behavior and battery size have a minor influence on the coincidence factor. Further, when mixing the parameters, such as EV battery size and rated charging power, then especially the active power drawn by the feeder does not change linearly. Ultimately, the study aims to add to the state-of-the-art by solely and systematically focusing on the CF and its sensitivity to a number of key factors. For planning and design, distribution system operators may use this study as a part of their planning for integration of electric vehicles in the electrical grid.