Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization

This article proposes a method for optimizing the energy systems in a distribution micro-grid using particle swarm optimization. The method considers the optimal production planning of simultaneous production systems and takes into account the loss of electric energy transmission resulting from the...

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Main Authors: Waleed Khalid Al-Azzawi, Ahmed Kateb Jumaah Al-Nussairi, Hussein Riyadh Taresh, Zainab R. Abdulsada, Kadhum Al-Majdi, Ali H. A, Julayeva Zhazira
Format: Article
Language:English
Published: OICC Press 2023-06-01
Series:Majlesi Journal of Electrical Engineering
Subjects:
Online Access:https://oiccpress.com/mjee/article/view/4996
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author Waleed Khalid Al-Azzawi
Ahmed Kateb Jumaah Al-Nussairi
Hussein Riyadh Taresh
Zainab R. Abdulsada
Kadhum Al-Majdi
Ali H. A
Julayeva Zhazira
author_facet Waleed Khalid Al-Azzawi
Ahmed Kateb Jumaah Al-Nussairi
Hussein Riyadh Taresh
Zainab R. Abdulsada
Kadhum Al-Majdi
Ali H. A
Julayeva Zhazira
author_sort Waleed Khalid Al-Azzawi
collection DOAJ
description This article proposes a method for optimizing the energy systems in a distribution micro-grid using particle swarm optimization. The method considers the optimal production planning of simultaneous production systems and takes into account the loss of electric energy transmission resulting from the concurrent production systems to the grid bus. The article establishes the correlation between the development of optimal load distribution methodology systems and the supply of electrical or thermal load. The advantages of the proposed algorithm have been demonstrated through numerical studies and comparisons, which showed a reduction in operational expenses, carbon dioxide emissions, and fuel consumption during both summer and winter seasons. The proposed method is an effective way of providing the required electrical energy of the sub-grid with minimal compliance requirements. The implementation of the proposed method during a single day and night in the summer season results in significant reductions of 17.5%, 13%, and 1% in operational expenses, carbon dioxide emissions, and fuel consumption, respectively. In the winter season, the pre-charge method also results in reductions of 10%, 7%, and 2% in operating cost, carbon dioxide emissions, and fuel consumption, respectively.
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institution OA Journals
issn 2345-377X
2345-3796
language English
publishDate 2023-06-01
publisher OICC Press
record_format Article
series Majlesi Journal of Electrical Engineering
spelling doaj-art-efec54bad07247c9bf4da860edc3e8962025-08-20T02:01:40ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962023-06-0117210.30486/mjee.2023.1987130.1147Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm OptimizationWaleed Khalid Al-Azzawi0Ahmed Kateb Jumaah Al-Nussairi1Hussein Riyadh Taresh2Zainab R. Abdulsada3Kadhum Al-Majdi4Ali H. A5Julayeva Zhazira6Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, IraqAl-Manara College for Medical Sciences, Amarah, IraqMazaya University College, IraqNational University of Science and Technology, Dhi Qar, IraqDepartment of Biomedical Engineering, Ashur University College, Baghdad, IraqDepartment of Medical Laboratory Technics, Al-Zahrawi University College, Karbala, Iraq050026, Almaty, Republic of Kazakhstan.This article proposes a method for optimizing the energy systems in a distribution micro-grid using particle swarm optimization. The method considers the optimal production planning of simultaneous production systems and takes into account the loss of electric energy transmission resulting from the concurrent production systems to the grid bus. The article establishes the correlation between the development of optimal load distribution methodology systems and the supply of electrical or thermal load. The advantages of the proposed algorithm have been demonstrated through numerical studies and comparisons, which showed a reduction in operational expenses, carbon dioxide emissions, and fuel consumption during both summer and winter seasons. The proposed method is an effective way of providing the required electrical energy of the sub-grid with minimal compliance requirements. The implementation of the proposed method during a single day and night in the summer season results in significant reductions of 17.5%, 13%, and 1% in operational expenses, carbon dioxide emissions, and fuel consumption, respectively. In the winter season, the pre-charge method also results in reductions of 10%, 7%, and 2% in operating cost, carbon dioxide emissions, and fuel consumption, respectively.https://oiccpress.com/mjee/article/view/4996Following the Electric LoadFollowing the Thermal LoadMicro-gridModified PWM methodOptimization
spellingShingle Waleed Khalid Al-Azzawi
Ahmed Kateb Jumaah Al-Nussairi
Hussein Riyadh Taresh
Zainab R. Abdulsada
Kadhum Al-Majdi
Ali H. A
Julayeva Zhazira
Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
Majlesi Journal of Electrical Engineering
Following the Electric Load
Following the Thermal Load
Micro-grid
Modified PWM method
Optimization
title Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
title_full Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
title_fullStr Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
title_full_unstemmed Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
title_short Optimization of Energy Systems in a Distribution Micro grid: An Application of the Particle Swarm Optimization
title_sort optimization of energy systems in a distribution micro grid an application of the particle swarm optimization
topic Following the Electric Load
Following the Thermal Load
Micro-grid
Modified PWM method
Optimization
url https://oiccpress.com/mjee/article/view/4996
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