Impacts of classified electric vehicle charging derived from driving patterns to the LV distribution network

Electric vehicles (EVs) charging demand is projected to be considerable in the future and imposes considerable impacts to the LV power network. However, how to forecast EV demand and assess the adverse charging effects like lower power quality and higher line loadings are still to be determined, which are crucial to economic power system operation and planning. In this research, by analysing the driving patterns of EVs, EV charging procedure is classified into 4 categories: residential slow charging (SC), workplace SC, fast charging (FC) and ultrafast charging (UC). The analysis criteria are mainly considering travelling distance, destination and vehicle idle time. Beta distribution function and double Gaussian distribution function are utilized to fit state of charge (SOC) and start charging time (SCT) functions of EV charging, from which the charging demand model of each EV charging type is given. Finally, time series power flow analysis is carried out to examine the adverse effects from EV charging demand in a test LV system.