Variability and uncertainty analysis of wood waste as a feedstock for gasification

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A reliable mathematical model will be developed and used to improve downdraft gasifier technology for converting landfill-diverted wood waste to heat and power. The model equations and associated statistical analysis will result in enhanced understanding of the inherent variability of wood waste and its influence on the performance of a gasifier, which produces bio-based fuel for electrical power generation. The model will be used to develop improved operating and automation strategies for the gasifier system, so that efficiency and feedstock flexibility can be improved. At Canadian landfill sites, there is currently a surplus of waste with a significant biogenic component (e.g., construction and demolition waste and wooden pallets). Recent studies show that downdraft gasification shows promise for utilization of these wood-based wastes as feedstock for generating heat and power. The proposed research will build on recent experimental and modeling research conducted by the two partner organizations: Natural Resources Canada (NRCan) and the National Research Council of Canada (NRC). An existing NRC model provides a reasonable qualitative description of gasifier behaviour, but improved estimates of kinetic and transport parameters used in the model are required so that the model can be validated and reliable quantitative predictions can be obtained. Statistical methods developed at Queen's University will be used with NRC gasifier data to obtain an updated model with improved parameter values. The improved model will then be used to guide new gasification experiments that will aid further model improvement. The resulting model will then be used to develop flexible operating and control strategies, which are needed to mitigate the effects of feedstock variability and to ensure reliable and economical process operation and gaseous fuel production.