Study on the slagging tendency estimation of biomass fuel combustion with different additives and pretreatment processes

Abstract

Grey fixed weight clustering (GFWC) method is studied to predict the slagging tendency of biomass fuels combustion. Then the results of the GFWC method were verified and compared with experimental results. In the experiment, bagasse was chosen as an example to prepare ash from three different pretreatment groups (non-washing (NW), water-washing (WW), acid-washing (AW)) and two samples adding kaolin and calcite respectively. The degree of slagging was determined by measuring the ash melting point temperature with the ash melting point analyzer and observing the structural morphology of the particles by the scanning electron microscope (SEM). The GFWC method was used to synthesize the five single slagging prediction indexes, and a mathematical model for the evaluation of slagging was proposed to improve the accuracy of the evaluation results. Furthermore, the accuracy and applicability of the GFWC method for the estimation of slagging tendency of 25 kinds of biomass were tested. Compared with SI method and ternary equilibrium phase diagram, the estimation of GFWC method can avoid the uncertainty and it agreed with the SEM characteristics and ash fusibility temperatures (AFT). This study provides a new reference for biofuel slagging trend estimation based on ash composition.