Co-firing multiple biomass types in coal-fired power plants presents complex analytical challenges that require a detailed understanding of fuel interactions and emission behaviors. Existing single-fuel methods are insufficient for predicting synergistic effects in ternary biomass-coal mixtures, necessitating the use of integrated experimental and computational strategies to optimize industrial-scale emissions. This study aimed to evaluate the performance of multi-biomass co-firing through combined thermogravimetric analysis (TGA) and computational fluid dynamics (CFD) modeling, measuring synergistic interactions and emission reduction potential in large-scale coal-fired boilers. Three multi-biomass mixtures were systematically analyzed: Mixture A (50% coal + 25% sawdust + 25% rice husk), Mixture B (50% coal + 25% rice husk + 25% SRF), and Mixture C (50% coal + 25% sawdust + 25% SRF). TGA experiments were conducted at heating rates of 10-40°C/min under oxygen and air atmospheres, while CFD simulations used a validated 600 MW Class CFPP (Coal Fired Power Plant) boiler model with 950,000 hexahedral elements and Rosin-Rammler particle distribution modeling. Beyond combustion efficiency, this research extends to sensitivity analysis of biomass ratios, economic feasibility, and long-term operational impacts such as fouling and erosion. TGA analysis showed strong synergistic effects with Mixture A, reaching the highest comprehensive combustion index (4.67) and peak reaction rate (13.08%/min), which was a 282% increase over the baseline coal. CFD simulations indicated significant emission reductions: CO₂ was lowered by 45.7% (Mixture C), SO₂ by 67.14% (Mixture A), and NOₓ by 30.71% (Mixture A). Model validation confirmed high accuracy, with only 3.59% error in O₂ concentration and 1.63% error in outlet temperature. The power derating ranged from 21.67% to 28.33%, with Mixture C exhibiting the best overall performance. The integrated TGA-CFD approach effectively quantifies multi-biomass synergistic interactions and emission reduction potential, providing critical insights for sustainable coal power operations and Indonesia's Net Zero Emissions 2060 goal.
Mochamad et al. (Thu,) studied this question.