EMPIRICAL BIOMASS TORREFACTION MODEL DEVELOPMENT FOR UTILIZING BIOMASS AS AN ALTERNATIVE SOLID FUEL

• Main Author: Husein Rahman, Muhammad
• Format: Final Project
• Language: Indonesia
• Subjects: Teknik (Rekayasa, enjinering dan kegiatan berkaitan)
• Online Access: https://digilib.itb.ac.id/gdl/view/47385
• Institution: Institut Teknologi Bandung

Biomass has a potential to be alternative solid fuel sources. However, biomass is not suitable used directly as solid fuel because of the biomass low calorific value. Torrefaction process could increase biomass calorific value. Torrefaction is a process to produce solid fuel at particular process parameter, which is temperature and loading time. At present parameter process data is not much available, but could be obtained from experiment or simulating biomass torrefaction process model. Torrefaction process modelling is still rarely done, but model could process various biomass, and need no physical experiment repetition. This research is intended to model biomass torrefaction process to predict torrefaction product and process energy requirement. This research torrefaction process modelling method is based on 3 points. Decomposition process for each organic biomass constituents (lignin, cellulose, hemicellulose, and extractives) occure independently. The model determines the torrefaction product, ultimate analysis, and calorific value, based on empirical data at temperature 200-300oC and residence time of 30 minute. The model calculates the process energy requirement based on organic component decomposition, sensible heating of organic component, water, and ash, and water vaporization. This model is simulated using 5 biomasses that has been tested before to verified the model validity. The model succeded to simulate various biomasses with temperature range 225–280oC. The model data output are solid product yield, carbon mass fraction, hydrogen, and oxygen, HHV, and energy yield, with deviation value of 11,38%, -10,64%, -10,81%, 10,51%, -12,53%, and -24,83% respectively. Model also produce process energy requirement data but not compared with testing results because the data is not available. The large deviation of energy yield is caused by extractives modelling.