@inproceedings{bf68ee8584bc43ef857276b350879a0a,
title = "A Multi-Objective Optimization Technique for Volt-Var Control with High PV Penetration using Genetic Algorithm",
abstract = "Voltage fluctuation issue is one of the primary challenges occurring with increasing PV penetration. Traditionally, voltage optimization was done with the use of Load Tap-Changing (LTC) transformers and capacitors. IEEE 1547a as amended in 2014 now allows the use of smart inverters on the distribution network by utility companies. This paper presents a co-optimization technique using Genetic Algorithm (GA) that uses an individual optimization algorithm of LTCs, shunt capacitors and smart inverters to determine the optimal settings for the devices. The PV smart inverters were set in the power factor control mode. The proposed technique was implemented on the IEEE 34 bus distribution feeder. The simulation results showed a reduction in the overall system power losses, minimized reactive power injection, optimal smart inverter power factor settings and ideal conservative voltage reduction.",
keywords = "Genetic Algorithm, High PV penetration, Optimization, Volt-VAR control",
author = "Olowu, \{Temitayo O.\} and Mohamadsaleh Jafari and Sarwat, \{Arif I.\}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 North American Power Symposium, NAPS 2018 ; Conference date: 09-09-2018 Through 11-09-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/NAPS.2018.8600557",
language = "English",
series = "2018 North American Power Symposium, NAPS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 North American Power Symposium, NAPS 2018",
}