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All Journal JUITA : Jurnal Informatika
Hilda Dwi Utari
Universitas Trisakti, Indonesia
Computer Science & IT

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Improve Coal Blending Optimization in CFPP by Cromosom and Fitness Function Redefinition of the Genetic Algorithm Binti Solihah; Ahmad Zuhdi; Abdul Rochman; Edo Yulistama; Hilda Dwi Utari
JUITA: Jurnal Informatika JUITA Vol. 12 No. 1, May 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i1.18731

Abstract

Blending coal before it enters the power plant boiler unit is necessary to adjust the coal categories according to the boiler unit specifications. The power plant must also comply with the regulations regarding coal-biomass co-firing through blending. Applying a Genetic Algorithm that only considers the composition and fitness based on the blend's quality leads to accumulation issues, decreasing coal quality. This research proposes redefining chromosomes, fitness functions, mutation rules, population determination, and output as the best chromosome used in the Genetic Algorithm. Testing uses various compositions of coal inputs from the barge, coal yard, and biomass to simulate different conditions. The test results demonstrate that the developed algorithm can provide all possible alternative blends between the coal in the barge and at the coal yard. Under specific conditions, operators can choose a blend composition that involves coal stored in the coal yard for an extended period.
Co-Authors Abdul Rochman Ahmad Zuhdi Binti Solihah Edo Yulistama