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首页> 外文会议>Combined Power Plant Air Pollutant Control Mega Symposium >Development of a Validated Model for Use in Minimizing NO{sub}x Emissions and Maximizing Carbon Utilization when Cofiring Biomass with Coal
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Development of a Validated Model for Use in Minimizing NO{sub}x Emissions and Maximizing Carbon Utilization when Cofiring Biomass with Coal

机译：开发验证模型，用于最小化NO {Sub} X排放，最大限度地利用煤炭煤炭

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摘要

In full-scale boilers, the effect of biomass cofiring on NO{sub}x and unburned carbon (UBC) emissions has been found to be site-specific. Indeed, few sets of field data are comparable and no consistent database of information exists upon which cofiring fuel choice or injection system design can be based to assure that NO{sub}x emissions will be minimized and UBC be reduced. This paper summarizes the results of a comprehensive project that generated an extensive set of pilot-scale test data that were used to validate a new predictive model for the cofiring of biomass and coal. All testing was performed at the 3.6 MMBtu/hr (1.75 MW{sub}t) Southern Company Services/Southern Research Institute Combustion Research Facility where a variety of burner configurations, coals, biomasses, and biomass injection schemes were utilized to generate a database of consistent, scalable, experimental results (～475 separate test conditions). This database was then used to validate a new model for predicting NO{sub}x and UBC emissions from the cofiring of biomass and coal. This model is based on an Advanced Post-Processing (APP) technique that generates an equivalent network of idealized reactor elements from a conventional CFD simulation. The APP reactor network is a computational environment that allows for the incorporation of all relevant chemical reaction mechanisms and provides a new tool to quantify NO{sub}x and UBC emissions for any cofired combination of coal and biomass.
机译：在满量规模的锅炉中，已发现生物量Cofiring对No {sub} x和未燃烧的碳（UBC）排放的影响是特定于目的。实际上，很少有几组现场数据是可比的，并且没有一致的信息数据库存在，其中COFIRING燃料选择或注射系统设计可以确保将最小化并且UBC降低。本文总结了一系列综合项目的结果，这些项目产生了广泛的导频尺度测试数据，用于验证生物质和煤炭的Cofiring的新预测模型。所有测试都在3.6 MMBTU / HR（1.75MW {Sub} T）南方公司服务/南方研究所燃烧研究设施，其中利用各种燃烧器配置，煤炭，生物量和生物量注射计划来生成数据库一致，可扩展，实验结果（〜475个单独的测试条件）。然后，该数据库用于验证用于预测NO {Sub} X和来自生物量和煤炭的Cofiring的UBC排放的新模型。该模型基于高级后处理（APP）技术，其从传统的CFD仿真生成了理想化的反应器元件的等效网络。 App Reactor网络是一种计算环境，允许加入所有相关的化学反应机制，并提供一种新工具，用于量化NO {Sub} X和UBC排放的煤和生物质的任何Cofired组合。

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