Multi-objective-optimization of process parameters of industrial-gas-turbine fueled with natural gas by using Grey-Taguchi and ANN methods for better performance

M. Gul; M.A. Kalam; M.A. Mujtaba; Saira Alam; M. Nasir Bashir; Iqra Javed; Umair Aziz; M. Rizwan Farid; M. Tahir Hassan; Shahid Iqbal

Energy Reports (Nov 2020)

Multi-objective-optimization of process parameters of industrial-gas-turbine fueled with natural gas by using Grey-Taguchi and ANN methods for better performance

M. Gul,
M.A. Kalam,
M.A. Mujtaba,
Saira Alam,
M. Nasir Bashir,
Iqra Javed,
Umair Aziz,
M. Rizwan Farid,
M. Tahir Hassan,
Shahid Iqbal

Affiliations

M. Gul: Center for Energy Science, Department of Mechanical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan; Corresponding author at: Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan.
M.A. Kalam: Center for Energy Science, Department of Mechanical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia; Corresponding author.
M.A. Mujtaba: Department of Mechanical Engineering, University of Engineering and Technology, New Campus Lahore, Pakistan
Saira Alam: Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan
M. Nasir Bashir: National University of Sciences and Technology (NUST), Karachi 75350, Pakistan
Iqra Javed: Department of Informatics and Systems, SST, University of Management and Technology, Lahore 54770, Pakistan
Umair Aziz: Department of Computer Engineering NFC IET Bahauddin Zakariya University, Multan 60000, Pakistan
M. Rizwan Farid: Department of Electrical Engineering, Faculty of Engineering and Technology, University of Gujrat, Pakistan
M. Tahir Hassan: Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan
Shahid Iqbal: Department of Computer Engineering, Faculty of Engineering and Technology Bahauddin Zakariya University, Multan 60000, Pakistan

Journal volume & issue: Vol. 6
pp. 2394 – 2402

Abstract

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Gas-turbines are widely utilized in the power generation sectors as these require low operational cost, have very good efficiencies among other turbines, and produce less pollution but required to improve their performances further. This study used efficient and simple optimization methods of grey Taguchi and ANN to enhance gas turbine performance. The objective was to increase ηth, horsepower, and to decrease SFC and heat release of the industrial gas turbine (model # T-4502) by optimizing different levels of input process parameters by gyey-Taguchi method. Finally, air inlet temperature of 28.8 °C,14400 rpm and cartridge filter were found as optimal input parameters at which gas turbine’s performance improved with less consumption of natural gas. Moreover, ANOVA analysis revealed that ‘air-inlet-temperature’ is the dominant and ‘type of air-inlet-filter’ is the least effective process parameter with 71.17% and 1.40% impacts on the output parameters of the gas turbine.Confirmatory test was carried out experimentally and by ANN at suggested optimal level of input parameters, satisfactory results obtained which validates the effectiveness of the grey-Taguchi-method.

Published in Energy Reports

ISSN: 2352-4847 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: http://www.journals.elsevier.com/energy-reports/

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