Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO

An efficient power control technique for inverter-based distributed generation (DG) in an islanded microgrid is investigated in this work. The objective is to raise the caliber of the electricity pumped from network-connected DGs. The characteristics that are taken into consideration include voltage...

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Main Authors: Masoud Dashtdar, Aymen Flah, Seyed Mohammad Sadegh Hosseinimoghadam, Ch Rami Reddy, Hossam Kotb, Kareem M. AboRas, Edson C. Bortoni
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9867998/
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author Masoud Dashtdar
Aymen Flah
Seyed Mohammad Sadegh Hosseinimoghadam
Ch Rami Reddy
Hossam Kotb
Kareem M. AboRas
Edson C. Bortoni
author_facet Masoud Dashtdar
Aymen Flah
Seyed Mohammad Sadegh Hosseinimoghadam
Ch Rami Reddy
Hossam Kotb
Kareem M. AboRas
Edson C. Bortoni
author_sort Masoud Dashtdar
collection DOAJ
description An efficient power control technique for inverter-based distributed generation (DG) in an islanded microgrid is investigated in this work. The objective is to raise the caliber of the electricity pumped from network-connected DGs. The characteristics that are taken into consideration include voltage and frequency control, dynamic response, and steady-state response, particularly when the microgrid is operating in island mode or when there is a load change. The control method consists of an internal current control loop and an external power control loop based on a synchronous reference frame and a conventional PI controller. The power controller is designed based on voltage-frequency (VF) control. In addition, an intelligent search technique that combines Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is utilized to automatically modify power controller parameters. The control technique in this research is that the DG modifies its control mode to modify the system voltage and frequency when the microgrid is islanded or load conditions change. The simulation results in MATLAB/SIMULINK software show that the proposed control system has been able to improve the power quality well.
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spelling doaj.art-16c6984c4fe94fbd8096d66f8815d8af2022-12-22T03:32:07ZengIEEEIEEE Access2169-35362022-01-011010535210536510.1109/ACCESS.2022.32018199867998Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSOMasoud Dashtdar0https://orcid.org/0000-0003-0301-3133Aymen Flah1https://orcid.org/0000-0002-3463-6096Seyed Mohammad Sadegh Hosseinimoghadam2Ch Rami Reddy3https://orcid.org/0000-0003-1941-0766Hossam Kotb4https://orcid.org/0000-0002-4052-6731Kareem M. AboRas5Edson C. Bortoni6https://orcid.org/0000-0001-9506-1268Electrical Engineering Department, Islamic Azad University—Bushehr Branch, Bushehr, IranNational School of Engineering of Gabes, University of Gabes, Gabes, TunisiaElectrical Engineering Department, Islamic Azad University—Bushehr Branch, Bushehr, IranElectrical and Electronics Engineering, Malla Reddy Engineering College, Maisammaguda, Secunderabad, IndiaDepartment of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, EgyptDepartment of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, EgyptElectric and Energy Systems Institute, Itajubá Federal University, Itajubá, BrazilAn efficient power control technique for inverter-based distributed generation (DG) in an islanded microgrid is investigated in this work. The objective is to raise the caliber of the electricity pumped from network-connected DGs. The characteristics that are taken into consideration include voltage and frequency control, dynamic response, and steady-state response, particularly when the microgrid is operating in island mode or when there is a load change. The control method consists of an internal current control loop and an external power control loop based on a synchronous reference frame and a conventional PI controller. The power controller is designed based on voltage-frequency (VF) control. In addition, an intelligent search technique that combines Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is utilized to automatically modify power controller parameters. The control technique in this research is that the DG modifies its control mode to modify the system voltage and frequency when the microgrid is islanded or load conditions change. The simulation results in MATLAB/SIMULINK software show that the proposed control system has been able to improve the power quality well.https://ieeexplore.ieee.org/document/9867998/MicrogridPI controllervoltage controlfrequency controlgenetic algorithmPSO
spellingShingle Masoud Dashtdar
Aymen Flah
Seyed Mohammad Sadegh Hosseinimoghadam
Ch Rami Reddy
Hossam Kotb
Kareem M. AboRas
Edson C. Bortoni
Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
IEEE Access
Microgrid
PI controller
voltage control
frequency control
genetic algorithm
PSO
title Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
title_full Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
title_fullStr Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
title_full_unstemmed Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
title_short Improving the Power Quality of Island Microgrid With Voltage and Frequency Control Based on a Hybrid Genetic Algorithm and PSO
title_sort improving the power quality of island microgrid with voltage and frequency control based on a hybrid genetic algorithm and pso
topic Microgrid
PI controller
voltage control
frequency control
genetic algorithm
PSO
url https://ieeexplore.ieee.org/document/9867998/
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