Modeling of the reburn process with the use of feedlot biomass as a reburn fuel

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2009-05-15

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Coal fired power plants will face many challenges in the near future as new regulations, such as the Clear Sky Act, are being implemented. These regulations impose much stricter limits on NOx emissions and plan to impose limits on mercury emissions from coal fired boilers. At this time no technologies are currently being implemented for control of Hg and this explains the strong interest in this area by the Department of Energy (DOE). Reburn technology is a very promising technology to reduce NOx emissions. Previous experimental research at TAMU reported that Feedlot Biomass (FB) can be a very effective reburn fuel, for reduction of NOx up to 90%-95%; however, little work has been done to model such a process with Feedlot Biomass as reburn fuel. The present work addresses the development of a reburn model to predict NOx and Hg emissions. The model accounts for finite rate of heating of solid fuel particles, mixing with NOx laden hot gases, size distribution, finite gas phase and heterogeneous chemistry, and oxidation and reduction reactions for NOx and Hg. To reduce the computational effort all the reactions, except those involved in mercury oxidation, are modeled using global reactions. Once the model was validated by comparison with experimental findings, extensive parametric studies were performed to evaluate the parameters controlling NOx reduction. From DOE research programs some experimental data regarding the capture of mercury from power plant is available, but currently no experimental data are available for Hg emission with reburn process. This model has shown a very large mercury reduction using biomass as a reburn fuel. The model recommends the following correlations for optimum reduction of NOx: Equivalence Ratio should be above 1.05; mixing time should be below 100ms (especially for biomass); pure air can be used as the carrier gas; the thermal power fraction of the reburner should be between 15% and 25%; residence time should be at least 0.5s and the Surface Mean Diameter (SMD) of the size distribution should be as small as possible, at least below 100 ?m.

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