Optimal composition of biomass pellet for enhancing calorific value using MOGA-ANN: a mixture of paddy straw, sawdust, cow dung, and paper pulp

Ali, Asad; Kumari, Mandeep; Laura, Jitender Singh; Rizwanullah, Mohammad; Manisha, .; Chhabra, Deepak; Sahdev, Ravinder Kumar

doi:10.1007/s13399-023-04490-5

Cited by 6 publications

(3 citation statements)

References 45 publications

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“…The present study was performed on MATLAB 2023a and is a typical case where multiple objectives are required to be optimized. A well-trained ANN model was used as the tness function in a Multi-Objective Genetic Algorithm (MOGA) to search for optimal tness values [15]. The decision variables and their upper and lower bounds were de ned rst.…”

Section: Ann-based Data Optimizationmentioning

confidence: 99%

“…A comprehensive exploration of agro-residue utilization for energy production using different routes was undertaken by researchers across various studies [11][12][13][14]. Agro-residues have low energy content and high alkali metal content and are required to be mixed with other biomasses to increase their suitability as fuel [15]. However, studies involving a mixture of agro-residues to increase its quality as fuel are limited.…”

Section: Introductionmentioning

confidence: 99%

“…Mainkaew et al [16] employed ANOVA and regression analysis, optimizing elephant dung, binder, and water ratios in briquette production, achieving a high calori c value of 17 MJ/kg. Ali et al [15] utilized ANOVA, regression, and ANN MOGA techniques to determine the optimal composition of paddy straw, sawdust, and binder, resulting in a 15.7 MJ/kg The present study proposes to conduct a feasibility study for the potential of a mixture of coal, charcoal, and residual forest biomass namely pine cone and pine needle, available in the region to address various issues related to power generation in thermal power plants and to assess the near future technical aspects for fuel availability. This is the rst and novel approach to study multiple fuel properties for mixed fuel systems leading to optimization of mixture design to address sustainability issues.…”

Section: Introductionmentioning

confidence: 99%

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A comprehensive analysis and optimization of coal-biomass mixed fuel for sustainable power generation

Datta,

Gajera,

Saikia

et al. 2024

Preprint

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Forest biomass in India remains grossly underutilized for bioenergy due to infrastructure, technological limitations, and competing land uses. Meghalaya, a state rich in forest cover, faces a similar issue. Additionally, with low-quality coal reserves available in Meghalaya, co-combustion with abundant forest biomass in thermal plants presents a practical solution for achieving energy independence in the state. A feasibility study explored the co-combustion of Meghalayan coal with pinewood charcoal, pine cone, and pine needle to increase calorific value while minimizing ash, sulphur, and chloride content. A multi-objective genetic algorithm utilising an artificial neural network and a response surface methodology model was developed to identify optimal mixture compositions corresponding to specified output criteria. By maximizing pine needle and pine cone usage while minimizing pinewood charcoal, an optimal mixture comprising 50% coal, 10% pinewood charcoal, 23.49% pine cone, and 16.52% pine needle was obtained. The optimal mixture yielded a maximum calorific value of 3873.70 kcal/kg, with minimum chloride (236.39 mg/kg), ash (32.05%), and sulphur (3444.7 mg/kg) content.

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Section: Ann-based Data Optimizationmentioning

confidence: 99%