Coincidence Factors for Domestic EV Charging From Driving and Plug-In Behavior

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