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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system

Article; controlled study; direct current; electric current; electric potential; electrical parameters; intermethod comparison; inverter; particle swarm optimization; performance; power quality performance; resistor inductor filter; software; total harmonic distortion; transient response time; volta...

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Main Authors: Roslan M.F., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Zuhdi A.W.M.
Other Authors: 57220188085
Format: Article
Published: Public Library of Science 2023
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spelling my.uniten.dspace-251092023-05-29T16:06:50Z Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system Roslan M.F. Al-Shetwi A.Q. Hannan M.A. Ker P.J. Zuhdi A.W.M. 57220188085 57004922700 7103014445 37461740800 56589966300 Article; controlled study; direct current; electric current; electric potential; electrical parameters; intermethod comparison; inverter; particle swarm optimization; performance; power quality performance; resistor inductor filter; software; total harmonic distortion; transient response time; voltage overshoot; algorithm; electricity; equipment design; power supply; renewable energy; Algorithms; Electric Power Supplies; Electricity; Equipment Design; Renewable Energy The lack of control in voltage overshoot, transient response, and steady state error are major issues that are frequently encountered in a grid-connected photovoltaic (PV) system, resulting in poor power quality performance and damages to the overall power system. This paper presents the performance of a control strategy for an inverter in a three-phase gridconnected PV system. The system consists of a PV panel, a boost converter, a DC link, an inverter, and a resistor-inductor (RL) filter and is connected to the utility grid through a voltage source inverter. The main objective of the proposed strategy is to improve the power quality performance of the three-phase grid-connected inverter system by optimising the proportional-integral (PI) controller. Such a strategy aims to reduce the DC link input voltage fluctuation, decrease the harmonics, and stabilise the output current, voltage, frequency, and power flow. The particle swarm optimisation (PSO) technique was implemented to tune the PI controller parameters by minimising the error of the voltage regulator and current controller schemes in the inverter system. The system model and control strategies were implemented using MATLAB/Simulink environment (Version 2020A) Simscape-Power system toolbox. Results show that the proposed strategy outperformed other reported research works with total harmonic distortion (THD) at a grid voltage and current of 0.29% and 2.72%, respectively, and a transient response time of 0.1853s. Compared to conventional systems, the PI controller with PSO-based optimization provides less voltage overshoot by 11.1% while reducing the time to reach equilibrium state by 32.6%. The consideration of additional input parameters and the optimization of input parameters were identified to be the two main factors that contribute to the significant improvements in power quality control. Therefore, the proposed strategy effectively enhances the power quality of the utility grid, and such an enhancement contributes to the efficient and smooth integration of the PV system. Copyright � 2020 Roslan et al. Final 2023-05-29T08:06:49Z 2023-05-29T08:06:49Z 2020 Article 10.1371/journal.pone.0243581 2-s2.0-85099070661 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099070661&doi=10.1371%2fjournal.pone.0243581&partnerID=40&md5=e78e0e32569e1dea99878146f073ec88 https://irepository.uniten.edu.my/handle/123456789/25109 15 12-Dec e0243581 All Open Access, Gold, Green Public Library of Science Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Article; controlled study; direct current; electric current; electric potential; electrical parameters; intermethod comparison; inverter; particle swarm optimization; performance; power quality performance; resistor inductor filter; software; total harmonic distortion; transient response time; voltage overshoot; algorithm; electricity; equipment design; power supply; renewable energy; Algorithms; Electric Power Supplies; Electricity; Equipment Design; Renewable Energy
author2 57220188085
author_facet 57220188085
Roslan M.F.
Al-Shetwi A.Q.
Hannan M.A.
Ker P.J.
Zuhdi A.W.M.
format Article
author Roslan M.F.
Al-Shetwi A.Q.
Hannan M.A.
Ker P.J.
Zuhdi A.W.M.
spellingShingle Roslan M.F.
Al-Shetwi A.Q.
Hannan M.A.
Ker P.J.
Zuhdi A.W.M.
Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
author_sort Roslan M.F.
title Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
title_short Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
title_full Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
title_fullStr Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
title_full_unstemmed Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system
title_sort particle swarm optimization algorithm-based pi inverter controller for a grid-connected pv system
publisher Public Library of Science
publishDate 2023
_version_ 1806427371511742464
score 13.222552

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