Master of Science
Levy, Edward K.
A study was undertaken to determine the feasibility of using advanced instrumentation and data processing to accurately predict in real-time the properties of biomass to be used as a supplemental fuel in coal-fired electric generating plants. Biomass use would reduce greenhouse gas emissions and also lower the fuel costs for a power plant. However, biomass properties are highly variable and not well characterized with a time scale that can be used for boiler operational control. Laser Induced Breakdown Spectroscopy (LIBS) was the analytical technique used in this study to analyze samples of biomass and coal. Spectral data obtained with LIBS were processed using advanced data processing techniques to determine fuel properties of interest.In this study, ash fusion temperature, high heating value, and ash mineral concentrations were measured. The results were highly successful by comparing the experimental results with independent laboratory analysis. All mineral results showed almost linear calibration curves with little data scatter. The heating value results, ranging from 6,620 Btu/lb to 13,080 Btu/lb, were obtained with root mean square error of approximately ±15 Btu/lb. The initial deformation ash fusion temperature, ranging from 1,590 to 2,800 ° F has a root mean square deviation of approximately ±33.34 ° F. These results showed that even under significant property variations, the combined application of LIBS and advanced data processing provides results that a power plant operator could use to mitigate problems in boilers fired with biomass and coal, which originate from the fuel quality variability of the feedstock.
Zhu, Tong, "Using LIBS and Advanced Data Processing to Analyze Biomass and Coal Feedstock for Utility Boiler Applications" (2013). Theses and Dissertations. 1704.