Title :
Impact of electric vehicles on LV feeder voltages
Author :
Yun Li ; Crossley, Peter A.
Author_Institution :
Sch. of Electr. & Electron. Eng., Univ. of Manchester, Manchester, UK
Abstract :
The impact of electric vehicles (EVs) on the voltages seen on a low voltage (LV) feeder are investigated in this paper. The Monte Carlo method was used to understand the impact of diversity of demand on LV feeders and especially the effect of uncontrolled human behavior. A statistical model of an EV was established to generate random high-resolution EV charging demand profiles. Moreover, both the balanced and unbalanced scenarios, with different EV charging locations, were investigated in a simulation study. The results were analyzed and used to illustrate how time of use tariffs can alleviate voltage drops and imbalance.
Keywords :
Monte Carlo methods; battery powered vehicles; electric potential; random processes; statistical analysis; tariffs; EV; LV feeder voltage; Monte Carlo method; electric vehicle; low voltage feeder; random high-resolution EV charging demand profile generation; statistical model; tariff; uncontrolled human behavior effect; voltage drop; voltage imbalance; Adaptation models; Batteries; Electricity; Load modeling; Monte Carlo methods; Substations; Monte Carlo methods; Voltage imbalance; demand side response; electric vehicles; low voltage network;
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
DOI :
10.1109/PESGM.2014.6938961
