Gas Turbine Performance Monitoring and Operation Challenges: A Review

• Main Authors: Yousif S., Alnaimi F., Thiruchelvam S.
• Other Authors: 57211393920
• Format: Review
• Published: Gazi Universitesi 2024
• Subjects: Fault; Gas Turbine; Machine learning; Sensor; Swirl; Cost effectiveness; Deep learning; Gases; Learning systems; Electrical power; Gas turbine performance; Machine-learning; Operational parameters; Parameter variable; Performance; Performance-monitoring; Power; Gas turbines
• Institution: Universiti Tenaga Nasional

Gas turbines efficiently produce high amounts of electrical power hence they have been widely deployed as dependable power generators. It has been detected that the performance of gas turbines is a function of plenty of operational parameters and environmental variables. The impacts of those variables on the said performance can be mitigated using powerful monitoring techniques. Thus, extra maintenance costs, component defect costs, and manpower costs can be illuminated. This paper has enlisted the factors impacting gas turbine efficiency. It has also reviewed multiple monitoring solutions for the said impacting factors, It has been concluded that all types of sensors have ignored errors in their work, which may exacerbate the problems of malfunctions in gas turbines due to the critical environment in which they operate (heat, fumes, etc.)