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

Abstract

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.