@article{ART003208673},
author={},
title={Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility},
journal={Carbon Letters},
issn={1976-4251},
year={2025},
volume={35},
number={2},
pages={709-727}
TY - JOUR
AU -
TI - Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility
JO - Carbon Letters
PY - 2025
VL - 35
IS - 2
PB - Korean Carbon Society
SP - 709
EP - 727
SN - 1976-4251
AB - The optimization of pellet fuels composed of rice straw, mustard straw, and sawdust was investigated in the present study to improve their properties and utility. Response surface methodology (RSM) and an artificial neural network (ANN) integrated with a multi-objective genetic algorithm (MOGA) were applied to optimize pellet composition for enhanced heating value and minimized ash, nitrogen, and sulfur content. An optimal blend of 74.40% rice straw, 15.60% mustard straw, and 10% sawdust was identified by RSM. These proportions were closely approximated by the MOGA-ANN model within ±1%, and the results were confirmed through experimental validation. Combustion ion chromatography was also used, to analyze the biomasses and the optimized blend, revealing reduced chloride (4189 mg/kg) and sulfur (2716 mg/kg) levels. These results were validated subsequently through experimental tests, confirming the accuracy of the proposed models. A techno-economic analysis indicated that a generation cost of Rs. 10.71 per unit would be associated with a fully agro-residue-based power plant, while less than Rs. 5.28–Rs. 5.31 would be the cost of generation per unit of electricity observed with 5% biomass co-firing in thermal plants. This study demonstrates that improved fuel quality and economic feasibility for biomass power generation can be achieved through strategic biomass blending and co-firing. These findings demonstrated that the blending of various biomass can be a viable strategy for enhancing the characteristics of pellet fuels on an industrial scale.
KW - Biomass Response surface methodology Artificial neural network Multi-objective optimization Combustion ion chromatography Techo-economic analysis
DO -
UR -
ER -
. (2025). Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility. Carbon Letters, 35(2), 709-727.
. 2025, "Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility", Carbon Letters, vol.35, no.2 pp.709-727.
"Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility" Carbon Letters 35.2 pp.709-727 (2025) : 709.
. Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility. 2025; 35(2), 709-727.
. "Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility" Carbon Letters 35, no.2 (2025) : 709-727.
. Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility. Carbon Letters, 35(2), 709-727.
. Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility. Carbon Letters. 2025; 35(2) 709-727.
. Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility. 2025; 35(2), 709-727.
. "Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility" Carbon Letters 35, no.2 (2025) : 709-727.
