Optimization of mixed agro residue pellets for enhanced fuel quality and economic feasibility

IF 5.5 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Bhautik Gajera, Arghya Datta, Anil Kumar Sarma, Mithilesh Kumar Jha
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Abstract

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.

Graphical abstract

Abstract Image

优化混合农渣颗粒提高燃料质量和经济可行性
对稻秆、芥菜秸秆和木屑组成的颗粒燃料进行了优化,以提高其性能和利用价值。采用响应面法(RSM)和结合多目标遗传算法(MOGA)的人工神经网络(ANN)对颗粒组成进行优化,以提高热值,降低灰分、氮和硫含量。RSM法确定了74.40%稻草、15.60%芥菜秸秆、10%木屑的最佳配比。这些比例被MOGA-ANN模型近似于±1%,并通过实验验证了结果。燃烧离子色谱法也用于分析生物质和优化后的混合物,揭示了降低的氯化物(4189 mg/kg)和硫(2716 mg/kg)水平。这些结果随后通过实验测试得到验证,证实了所提出模型的准确性。一项技术经济分析表明,一个完全基于农业残留物的发电厂的发电成本为每台10.71卢比,而低于5.28卢比。5.31将是在火力发电厂中观察到的5%生物质共烧的每单位电力的发电成本。该研究表明,通过战略性生物质混合和共烧,可以提高生物质发电的燃料质量和经济可行性。这些发现表明,在工业规模上,混合各种生物质可以成为提高颗粒燃料特性的可行策略。图形抽象
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来源期刊
Carbon Letters
Carbon Letters CHEMISTRY, MULTIDISCIPLINARY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
7.30
自引率
20.00%
发文量
118
期刊介绍: Carbon Letters aims to be a comprehensive journal with complete coverage of carbon materials and carbon-rich molecules. These materials range from, but are not limited to, diamond and graphite through chars, semicokes, mesophase substances, carbon fibers, carbon nanotubes, graphenes, carbon blacks, activated carbons, pyrolytic carbons, glass-like carbons, etc. Papers on the secondary production of new carbon and composite materials from the above mentioned various carbons are within the scope of the journal. Papers on organic substances, including coals, will be considered only if the research has close relation to the resulting carbon materials. Carbon Letters also seeks to keep abreast of new developments in their specialist fields and to unite in finding alternative energy solutions to current issues such as the greenhouse effect and the depletion of the ozone layer. The renewable energy basics, energy storage and conversion, solar energy, wind energy, water energy, nuclear energy, biomass energy, hydrogen production technology, and other clean energy technologies are also within the scope of the journal. Carbon Letters invites original reports of fundamental research in all branches of the theory and practice of carbon science and technology.
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