Optimisasi Time Interval Sootblower untuk Meningkatkan Performa Pembakaran pada Pulverized Coal Boiler Menggunakan Metode Stochastic Algorithm

Wiradarma, Ilham (2025) Optimisasi Time Interval Sootblower untuk Meningkatkan Performa Pembakaran pada Pulverized Coal Boiler Menggunakan Metode Stochastic Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5009211099-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy

Abstract

Efisiensi pembakaran pada Pulverized Coal Boiler sangat dipengaruhi oleh fouling, yaitu penumpukan jelaga yang menghambat perpindahan panas. Pembersihan dengan sootblower sering kali dioperasikan secara manual tanpa mempertimbangkan kondisi aktual, sehingga menyebabkan pemborosan energi dan keausan peralatan. Maka dari itu, penelitian ini diajukan untuk mengoptimalkan interval waktu sootblower menggunakan algoritma stokastik dengan mempertimbangkan resistansi termal sebagai indikator fouling secara time series. Hasil penelitian menunjukkan bahwa fouling pada superheater platen terjadi lebih cepat dibandingkan LTSH, terutama pada beban tinggi. Optimisasi waktu sootblower menghasilkan interval optimal yang lebih pendek dari siklus existing. Dengan penerapan optimisasi ini, performa perpindahan panas meningkat. Ditunjukkan oleh kenaikan overall heat transfer coefficient sebesar 2,62% pada superheater high load, 2,54% pada superheater low load, 1,22% pada LTSH high load, dan 1,59% pada LTSH low load. Peningkatan efisiensi ini menghasilkan cost saving berturut-turut sebesar 14,78%, 16,79%, 20,81%, dan 30,29% secara berurutan pada skenario-skenario tersebut. Model ini memungkinkan operasi sootblower dilakukan secara lebih efisien dan berbasis data, sehingga memberikan manfaat ekonomi dan keandalan pada sistem pembangkit listrik.
=====================================================================================================================================
The combustion efficiency of Pulverized Coal Boilers is significantly influenced by fouling, which is the accumulation of soot that impedes heat transfer. Sootblower operations are often executed manually without considering the actual fouling condition, leading to unnecessary energy consumption and equipment wear. Therefore, this study aims to optimize sootblower intervals using a stochastic algorithm, with thermal resistance modeled as a time-series indicator of fouling severity. The results show that fouling develops more rapidly on the superheater platen compared to the LTSH, especially under high load conditions. The optimized sootblower intervals are shorter than the existing cycles. With the implementation of this optimization, heat transfer performance improves, as indicated by an increase in the overall heat transfer coefficient of 2.62% in the superheater high load scenario, 2.54% in the superheater low load, 1.22% in the LTSH high load, and 1.59% in the LTSH low load. These improvements result in corresponding cost savings of 14.78%, 16.79%, 20.81%, and 30.29%, respectively. This model enables sootblower operations to be executed more efficiently and data-driven, providing both economic benefits and improved reliability for power plant systems.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Cost Saving, Fouling, Sootblower, Pulverized Coal Boiler, Resistansi Termal, Stochastic Algorithm.
Subjects:	Q Science > QA Mathematics > QA402.5 Genetic algorithms. Interior-point methods. Q Science > QA Mathematics > QA9.58 Algorithms Q Science > QC Physics > QC100.5 Measuring instruments (General) Q Science > QC Physics > QC151 Fluid dynamics Q Science > QC Physics > QC320 Heat transfer T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T58.62 Decision support systems T Technology > T Technology (General) > T58.8 Productivity. Efficiency T Technology > TA Engineering (General). Civil engineering (General) > TA462 Metal Corrosion and protection against corrosion T Technology > TJ Mechanical engineering and machinery > TJ263.5 Boilers (general) T Technology > TJ Mechanical engineering and machinery > TJ265.E23 Thermodynamics. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001 Production of electric energy or power T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1322.6 Electric power-plants
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Ilham Wiradarma
Date Deposited:	24 Jul 2025 07:55
Last Modified:	24 Jul 2025 07:55
URI:	http://repository.its.ac.id/id/eprint/120287

Actions (login required)

View Item