Thermodynamic Simulation of Fouling and Erosion in an Industrial Gas Turbine for Power Generation Applications

Document Type : Propulsion and Heat Transfer

Authors

1 Ph.D. Student, Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

2 Corresponding author: Professor, Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

In this research, the performance deterioration caused by the degradation of the main gas path components is simulated for the IGT25 industrial gas turbine. To this aim, after developing a thermodynamic model of IGT25 and verifying the model with real data it is applied to simulate the performance deterioration of the gas turbine. Considering the fouling and erosion as two common gas path faults, these two faults are simulated by deviating the flow capacity and isentropic efficiency and their effects on the performance parameters in the power turbine speed control mode are investigated. The results reveal that the occurrence of fouling on the compressor blade in the investigated control mode leads to a decrease in the gas generator turbine speed, fuel flow, compressor exhaust temperature, gas generator turbine inlet temperature, power turbine inlet temperature and exhaust gas temperature contrarily an increase occurs in air mass flow, compressor exit pressure and power turbine inlet pressure. According to the results, the maximum deviation from the normal condition due to fouling and erosion of the compressor blades observed in the exhaust gas temperature, which is 3.8% and 2.2%, respectively. It is found that the operating conditions of the gas turbine affect the amount of deviation of the performance parameters when a gas path fault occurs.

Highlights

  • The IGT25 industrial gas turbine modeling for power generation applications using T-MATS.
  • Simulation of performance deterioration.
  • Simulation of fouling and erosion in gas path components
  • Investigating the effect of deterioration on performance parameters in different loadings

Keywords


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[1] Hanachi H, Mechefske C, Liu J, Banerjee A, Chen Y. Performance-Based Gas Turbine Health Monitoring, Diagnostics, and Prognostics: A Survey. IEEE Transactions on Reliability. 2018;67(3):1340-63##.
[2] Melino F, Morini M, Peretto A, Pinelli M, Ruggero Spina P. Compressor fouling modeling: relationship between computational roughness and gas turbine operation time. Journal of engineering for gas turbines and power. 2012;134(5)##.
[3] Abass KO. Techno-Economic Analysis of Gas Turbine Compressor Washing to Combat Fouling. 2015##.
[4] Meher-Homji CB, Chaker MA, Motiwala HM, editors. Gas Turbine Performance Deterioration. Proceedings of the 30th turbomachinery symposium; 2001: Texas A&M University. Turbomachinery Laboratories##.
[5] Urban LA. Gas turbine engine parameter interrelationships: Hamilton Standard Division of United Aircraft Corporation; 1969##.
[6] Saravanamuttoo H, MacIsaac B. Thermodynamic models for pipeline gas turbine diagnostics. 1983##.
[7] Aker G, Saravanamuttoo H. Predicting gas turbine performance degradation due to compressor fouling using computer simulation techniques. 1989##.
[8] Marschal D, Muir D, Saravanamuttoo H. Health monitoring of variable geometry gas turbines for the Canadian navy. The American Society of Mechanical Engineers.345##.
[9] Provost M, editor COMPASS: a generalized ground-based monitoring system. COMADEM 89 International: Proceedings of the First International Congress on Condition Monitoring and Diagnostic Engineering Management (COMADEM); 1989: Springer##.
[10] Kurz R, Brun K. Degradation in gas turbine systems. J Eng Gas Turbines Power. 2001;123(1):70-7##.
[11] Lee JJ, Kim TS. Development of a gas turbine performance analysis program and its application. Energy. 2011;36(8):5274-85##.
[12] Mohammadi E, Montazeri-Gh M. Simulation of full and part-load performance deterioration of industrial two-shaft gas turbine. Journal of Engineering for Gas Turbines and Power. 2014;136(9)##.
[13] Kim TS. Model-based performance diagnostics of heavy-duty gas turbines using compressor map adaptation. Applied energy. 2018;212:1345-59##.
[14] Liu Z, Karimi IA. Gas turbine performance prediction via machine learning. Energy. 2020;192:116627##.
[15] Salilew WM, Abdul Karim ZA, Lemma TA, Fentaye AD, Kyprianidis KG. Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine. Entropy. 2022;24(8):1052##.
[16] Nordström L. Construction of a Simulator for the Siemens Gas Turbine SGT-600. Institutionen för systemteknik; 2005##.
[17] Montazeri-Gh M, Nekoonam A. Gas path component fault diagnosis of an industrial gas turbine under different load condition using online sequential extreme learning machine. Engineering Failure Analysis. 2022;135:106115##.
[18] Soares C. Gas turbines: a handbook of air, land and sea applications: Elsevier; 2011##.
[19] Chapman JW, Lavelle TM, May RD, Litt JS, Guo T-H. Toolbox for the modeling and analysis of thermodynamic systems (T-MATS) user's guide. 2014##.
[20] Gilani SI-u-H, Baheta AT, Rangkuti C, editors. Study the effect of variable vanes on performance of axial compressor for single shaft gas turbine cogeneration plant. 2009 3rd International Conference on Energy and Environment (ICEE); 2009: IEEE##.
[21] Montazeri-Gh M, Fashandi SAM. Application of Bond Graph approach in dynamic modelling of industrial gas turbine. Mechanics & Industry. 2017;18(4):410##.
[22] Escher P. Pythia: An object-orientated gas path analysis computer program for general applications. 1995##.
[23] Patel V, Kadirkamanathan V, Kulikov G, Arkov V, Breikin T, editors. Gas turbine engine condition monitoring using statistical and neural network methods. IEE Colloquium on Modeling and Signal Processing for Fault Diagnosis (Digest No: 1996/260); 1996: IET##.
[24] Romessis C, Mathioudakis K, editors. Implementation of stochastic methods for industrial gas turbine fault diagnosis. Turbo Expo: Power for Land, Sea, and Air; 2005##.