The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review

This study aims to review the use of artificial intelligence applications in the management of gas turbine stations and their impact on enhancing and raising the efficiency of these stations, including managing the stations themselves, then improving operational efficiency, predicting faults, and de...

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Main Authors: Ali Fadiel, Moktar Mohamad, Hafiez Khalid, Younis Esham
Format: Article
Language:English
Published: Unviversity of Technology- Iraq 2025-07-01
Series:Engineering and Technology Journal
Subjects:
Online Access:https://etj.uotechnology.edu.iq/article_188001_dad0a4378ba005dd4651b63fec3a4c1b.pdf
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author Ali Fadiel
Moktar Mohamad
Hafiez Khalid
Younis Esham
author_facet Ali Fadiel
Moktar Mohamad
Hafiez Khalid
Younis Esham
author_sort Ali Fadiel
collection DOAJ
description This study aims to review the use of artificial intelligence applications in the management of gas turbine stations and their impact on enhancing and raising the efficiency of these stations, including managing the stations themselves, then improving operational efficiency, predicting faults, and developing strategies for road maintenance and precautionary maintenance while reducing the cost through a methodology that is a combination. One of several methodologies describes the factors that influence the enhancement of operational efficiency and management of turbine plants using artificial intelligence applications. The quantitative methodology in collecting data and studies that included the subject and the analytical and comparative methods in comparing studies and analyzing the most critical results reached, as the article relies on an analysis of scientific literature and recent studies to clarify the potential benefits and challenges associated with the application of artificial intelligence in this field. The review discusses the artificial intelligence tools employed, including machine learning and neural networks, and highlights future innovations that may enhance the efficiency of turbine systems. The study concludes by discussing current limitations and providing recommendations for research and development in this promising field. Most studies have indicated that artificial intelligence applications play a significant role in enhancing the management of gas turbine plants, increasing operational efficiency by 3 to 5%, and reducing operating costs by 8 to 15%.
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publishDate 2025-07-01
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spelling doaj-art-b2201108e5cf48d9a5ca17f59db3327a2025-08-20T03:18:38ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582025-07-0143753654510.30684/etj.2025.157633.1904188001The impact of using artificial intelligence techniques on the performance of turbine stations: A mini reviewAli Fadiel0Moktar Mohamad1Hafiez Khalid2Younis Esham3Department of Mechanical Engineering, Higher Institute of Science and Technology-Tobruk, Libya.Department of Mechanical Engineering, Higher Institute of Science and Technology-Tobruk, Libya.Department of Mechanical Engineering, Higher Institute of Science and Technology-Tobruk, Libya.Department of Mechanical Engineering, Higher Institute of Science and Technology-Tobruk, Libya.This study aims to review the use of artificial intelligence applications in the management of gas turbine stations and their impact on enhancing and raising the efficiency of these stations, including managing the stations themselves, then improving operational efficiency, predicting faults, and developing strategies for road maintenance and precautionary maintenance while reducing the cost through a methodology that is a combination. One of several methodologies describes the factors that influence the enhancement of operational efficiency and management of turbine plants using artificial intelligence applications. The quantitative methodology in collecting data and studies that included the subject and the analytical and comparative methods in comparing studies and analyzing the most critical results reached, as the article relies on an analysis of scientific literature and recent studies to clarify the potential benefits and challenges associated with the application of artificial intelligence in this field. The review discusses the artificial intelligence tools employed, including machine learning and neural networks, and highlights future innovations that may enhance the efficiency of turbine systems. The study concludes by discussing current limitations and providing recommendations for research and development in this promising field. Most studies have indicated that artificial intelligence applications play a significant role in enhancing the management of gas turbine plants, increasing operational efficiency by 3 to 5%, and reducing operating costs by 8 to 15%.https://etj.uotechnology.edu.iq/article_188001_dad0a4378ba005dd4651b63fec3a4c1b.pdfartificial intelligence applicationsgas turbinesoperational efficiencycost reductionmanagement
spellingShingle Ali Fadiel
Moktar Mohamad
Hafiez Khalid
Younis Esham
The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
Engineering and Technology Journal
artificial intelligence applications
gas turbines
operational efficiency
cost reduction
management
title The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
title_full The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
title_fullStr The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
title_full_unstemmed The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
title_short The impact of using artificial intelligence techniques on the performance of turbine stations: A mini review
title_sort impact of using artificial intelligence techniques on the performance of turbine stations a mini review
topic artificial intelligence applications
gas turbines
operational efficiency
cost reduction
management
url https://etj.uotechnology.edu.iq/article_188001_dad0a4378ba005dd4651b63fec3a4c1b.pdf
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