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Alviansyah Putra Wahyudi
Politeknik Negeri Jakarta

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Analisis Deviasi Specific Fuel Consumption (SFC) Dan Efisiensi Termal Turbin Gas Kondisi Baseline Serta Implikasinya Terhadap Biaya Bahan Bakar Alviansyah Putra Wahyudi; Arifia Ekayuliana; Gun Gun Ramdlan Gunadi; Fathan Mubina Dewadi
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Gas turbine performance degradation caused by changes in ambient temperature and compressor deterioration can increase Specific Fuel Consumption (SFC), reduce thermal efficiency, and increase fuel costs. Previous studies have investigated the influence of ambient temperature and compressor washing on gas turbine performance; however, most have evaluated these factors separately without relating them to deviations from the manufacturer’s baseline and their economic implications under relatively constant operating load conditions. This study proposes an integrated evaluation approach by combining the effects of ambient temperature, compressor condition before and after compressor washing, performance deviation from the manufacturer’s baseline, and its impact on fuel cost. The study aims to analyze the deviations in Specific Fuel Consumption (SFC) and thermal efficiency from the manufacturer’s baseline and to evaluate their implications for fuel cost using actual operating data based on the Brayton cycle approach. The results show that the SFC deviation decreased from 4.64–4.72% before compressor washing to 3.56–3.79% after compressor washing, while the thermal efficiency deviation improved from −1.29% to −1.66% to −0.85% to −1.12%. These performance improvements were accompanied by a 0.84–1.06% reduction in fuel cost under all operating conditions. The findings provide quantitative evidence that deviation evaluation based on the manufacturer’s baseline can be used as an effective approach to assess the effectiveness of compressor washing and to support condition-based maintenance decision-making for gas turbines.