Near-Infrared Spectroscopy and Extractive Probe Sampling for Biomass and Combustion Characterization

• Biomass is characterized by highly variable properties. It can be converted to more valuable energy forms and products through a variety of conversion processes. This thesis focuses on addressing several important issues related to combustion and pulping.Experimental investigations were carried out on a biomass-fired industrial fluidized-bed boiler. The observed combustion asymmetry was explained by an imbalance in the fuel feed. Increased levels of carbon monoxide were detected close to boiler walls which contribute significantly to the risk of wall corrosion.Moreover, extensive literature analysis showed that near-infrared spectroscopy (NIRS) has a great potential to provide property information for heterogeneous feedstocks or products, and to directly monitor processes producing/processing biofuels in real-time. The developed NIRS-based models were able to predict characteristics such as heating value, ash content and glass content. A study focusing on the influence of different spectra acquisition parameters on lignin quantification was carried out. Spectral data acquired on moving woodchips were found to increase the representativeness of the spectral measurements leading to improvements in model performance.The present thesis demonstrates the potential of developing NIRS-based soft-sensors for characterization of biomass properties. The on-line installation of such sensors in an industrial setting can enable feed-forward process control, diagnostics and optimization.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Kemiteknik -- Kemiska processer (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Chemical Engineering -- Chemical Process Engineering (hsv//eng)

Keyword

Energy- and Environmental Engineering

energi- och miljöteknik

Publication and Content Type

vet (subject category)

dok (subject category)