Power quality enhancement by mitigating load imbalance from random electric vehicle fleet at electric vehicle charging stations
Nitin Kumar Saxena, Wenzhong Gao
Abstract
To promote the widespread adoption of Electric Vehicles (EVs), various measures are being implemented at every level of the power system hierarchy. The exponential growth of EVs in the transportation sector has overloaded the existing grid, necessitating solutions to optimize its capabilities. Electric Vehicle Charging Stations (EVCS) power demand can be satisfied with a low-voltage distribution network that addresses issues of local VAR demand and power quality. D-STATCOM, as a reactive power compensator, and load balancing are two key factors that can play a vital role at EVCS. This paper models a 180 kW charging station with a 15 kW, 120 V base load and fifteen charging guns of 11 kW, 240 V each. A random fleet of EVs is considered throughout the day, and a solution is proposed to enhance power quality and manage local reactive power by balancing the random load of EVs with D-STATCOM. Results for the EV random fleet are compared with load balancing proposals in terms of low voltage distribution network (LVDN) node’s important considerations like real and reactive power balance at EVCS, frequency and voltage deviations at EVCS, and power quality measures such as total harmonic distortion, current, and voltage imbalances. The results are also tested for seasonal demand of winter and summer, including peak demand for the day too. • Simulink-based EVCS with a detailed D-STATCOM model for the inclusion of a random EV fleet • Reactive power management at EVCS using D-STATCOM • Planning of EVCS for a random EV fleet throughout the day • Power quality improvement with the proposed EVs scheduling