A study on the scaled intelligent supply mode of biomass briquette fuel in China.

Abstract

In the backdrop of China's 'Carbon peak, Carbon neutrality' goal, to reduce the pollution caused by carbon emissions to the atmosphere, this study investigates the supply of biomass briquette fuel. The supply of biomass briquette fuel is generally divided into two stages: the first stage involves the collection, storage, and transportation of biomass straw to the biomass briquette production base; the second encompasses the processing of the biomass straw into briquette fuel at the production base, followed by its transportation to the biomass boiler heating center for utilization. In this paper, a mathematical model is developed based on carbon emission and economic cost. The model is then calculated with an optimized intelligent algorithm, and the results are subjected to sensitivity analysis. The results demonstrate that: (1) Compared to the pre-optimization phase, the optimized model increases profits by 26.31 % and reduces carbon emissions by 12.64 %. (2) The adaptive genetic algorithm shows significantly better convergence speed and accuracy compared to the traditional genetic algorithm, making it more suitable for intelligent calculations of biomass briquette fuel supply. (3) As the weight coefficient of carbon emissions increases, economic costs continue to decrease with increasing sensitivity, while carbon emissions continue to decrease with decreasing sensitivity. These results provide references for further optimizing the weight coefficients of economic costs and carbon emissions in the supply of briquette fuel. This study contributes to reducing carbon emissions and provide references for the rational and intelligent supply of biomass briquette fuel.