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All Journal International Journal of Research in Vocational Studies (IJRVOCAS)
Akbar Imam
Universitas Tridinanti
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Analysis of Parameters That Affect the Efficiency of Gas Power Plants Deka Darma Saputra; Muhammad Amin Fauzie; Raden Kohar; Akbar Imam; Martin Lutther King; Muhammad Lazim
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 3 No. 1 (2023): IJRVOCAS - April
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v3i1.197

Abstract

This study aims to analyze the parameters that actively affect the efficiency of gas power plants in order to optimize their performance. The method used in this study was an analytical approach based on the results of performance tests conducted in 2018, 2020, and 2022 on gas power plants in the sumatera selatan area, based on thermodynamic equations. Based on the results of the study, it is explained that there is a very significant relationship between the inlet air temperature of the compressor, the inlet fuel temperature, and the turbine exhaust temperature and active power to the efficiency of gas-fired power plants, where an increase in the inlet air temperature to the compressor will reduce the compressor efficiency, which is predicted using linear regression with an R2=0.82. An increase in the exhaust temperature and active power will significantly reduce the thermal cycle efficiency, which is predicted using linear regression with an average R2 =0.96. In addition, an increase in the fuel mass flow rate and inlet fuel temperature will increase the turbine efficiency, which is predicted using linear regression with an average R2 =0.97. Therefore, the relationships obtained in this study can be used as a reference for energy companies and governments in developing more efficient gas-fired power plants in the future
Co-Authors Deka Darma Saputra Martin Lutther King Muhammad Amin Fauzie Muhammad Lazim Raden Kohar