Research on the Optimization of Co-Pyrolysis Process Based on Multiple Linear Regression and SA Algorithm

This paper investigates the optimization of the co-pyrolysis process of biomass and coal, aiming to enhance tar yield and energy conversion efficiency. Initially, we conducted preprocessing and correlation analysis on the collected pyrolysis dataset to assess the impact of n-hexane insolubles (INS) on tar, water, and coke yields. Subsequently, a multivariate linear regression model incorporating INS, mixing ratio, and their interaction term was developed to explore the combined effects of these factors on pyrolysis yields. The simulated annealing algorithm was employed to optimize INS and mixing ratios to maximize tar yield. The results indicated that when the concentration of INS reached 0.99, the tar yield peaked.