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

Energy Reports

卷:6

M.A. Mujtaba¹  M. Nasir Bashir²  M.A. Kalam³  M. Gul⁴  Saira Alam⁴  Shahid Iqbal⁵  M. Tahir Hassan⁶  Umair Aziz⁷  Iqra Javed⁸  M. Rizwan Farid⁹ 

[1] Corresponding author at: Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan.;

[2] Corresponding author.;

[3] Department of Mechanical Engineering, Faculty of Engineering and technology Bahauddin Zakariya University, Multan 60000, Pakistan;

[4] Center for Energy Science, Department of Mechanical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia;

[5] Department of Computer Engineering NFC IET Bahauddin Zakariya University, Multan 60000, Pakistan;

[6] Department of Informatics and Systems, SST, University of Management and Technology, Lahore 54770, Pakistan;

[7] Department of Mechanical Engineering, University of Engineering and Technology, New Campus Lahore, Pakistan;

[8] National University of Sciences and Technology (NUST), Karachi 75350, Pakistan;

关键词: Gas turbine;    Grey Taguchi optimization;    Grey relational analysis;    ANOVA analysis;    Artificial neural networking;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown