A Novel Hybrid RERNN-SCSO Technique-based Unified Power Quality Conditioner of Microgrid in an EV Charging Station

Ch S.V.Prasada Rao, Alagappan Pandian, Ch Rami Reddy*, Muhammad Majid Gulzar, Muhammad Khalid*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


According to recent power quality studies, voltage sags and voltage unbalance in medium-voltage and low-voltage distribution grids are the most common type of power quality problems. Power quality is an essential concern in the modern power system that can affect consumers and utility. In modern age, with an increase in sensitive and expensive electronic equipment, power quality is essential for the power system’s reliable and safe operation. This paper proposes a hybrid technique-based unified power quality conditioner (UPQC) of microgrid in an EV charging station (EVCS), and it is the combination of recalling-enhanced recurrent neural network (RERNN) and sand cat swarm optimization (SCSO), together called as RERNN-SCSO. The SCSO creates the converter control signal, and the RERNN method forecasts the control signal from SCSO method. The proposed technique consists of series-active power filter (Se-APF), shunt-active power filter (Sh-APF), and DC-side capacitor as the parts of proposed technique. The major purpose of RERNN-SCSO technique is used to increase the power quality. Many loads, like highly inductive NLL, nonlinear loads (NLL) as well as unbalanced NLL (UNLL), are all linked at the point of common coupling (PCC). When the major structure of UPQC is built into the EVCS, an additional alternating current (AC)/DC converter will help with initialization. At this, the charging position provides charging service to the EVs as well as discharges the EVs into the power grid. The novelty of the proposed work consists in connecting EVs in parallel to the UPQC DC-side using double-layer microgrid (MC) and DC–DC converter. The proposed method ensures EV charging while efficiently handling quality of power issues like harmonic current, voltage disturbance, voltage sag and swell and voltage unbalance. RERNN-SCSO method performance is performed on the MATLAB/Simulink software to analyze the working performances and related with present techniques. RERNN-SCSO method-based THD under voltage sag condition as 2.03% and swell as 2.01%, which is lower than the existing methods.

Original languageEnglish
Pages (from-to)7277-7306
Number of pages30
JournalArabian Journal for Science and Engineering
Issue number5
StatePublished - May 2024

Bibliographical note

Publisher Copyright:
© King Fahd University of Petroleum & Minerals 2024.


  • Converter
  • Distribution system
  • Electric vehicle charging stations
  • Photovoltaic (PV)
  • Smart grid (SG)
  • UPQC

ASJC Scopus subject areas

  • General


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