TY  - JOUR
AU  - Saxena, Nitin Kumar
AU  - Gao, David Wenzhong
PY  - 2025
TI  - Power quality enhancement by mitigating load imbalance from random electric vehicle fleet at electric vehicle charging stations
JO  - Green Energy and Intelligent Transportation
SN  - 2097-2512
VL  - 4
IS  - 4
AB  - 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.
UR  - https://doi.org/10.1016/j.geits.2024.100222
DO  - 10.1016/j.geits.2024.100222