基于烟气参数对SNCR还原剂雾化粒径和喷入量的模拟优化

发布时间：2018-03-14 21:09

本文选题：选择性非催化还原　切入点：雾化粒径　出处：《化工进展》2017年02期 　论文类型：期刊论文

【摘要】：为降低烟气参数的不均匀分布对选择性非催化还原(SNCR)脱硝的影响,对220MW燃煤锅炉烟气状态分布特征及其对脱硝效果的影响进行数值研究,同时探讨了还原剂雾化粒径和喷入量的优化方案。研究表明,为保证还原剂在温度窗口内具有充足的反应时间,液滴的最佳平均粒径随高度而改变;此外,由于还原剂喷入区域烟气存在旋流作用,还原剂随烟气向炉膛局部"富集",导致出口NH_3/NO分布不均匀。据此,提出了喷枪雾化参数的优化策略:1对不同高度处液滴的平均雾化粒径进行分层优化;2在固定氨氮摩尔比下,根据旋流特征调整不同区域喷枪的流量分配。模拟结果显示,氨氮摩尔比保持1.2时,相比电站基准工况,优化方案能够将脱硝率从36.8%提高到42.1%,漏氨量降低49%;此外,随着氨氮摩尔比的增大,优化方案体现出更好的脱硝效果,但是优化程度略有降低。
[Abstract]:In order to reduce the effect of non-uniform distribution of flue gas parameters on the denitrification of selective non-catalytic reduction (SNCR), the characteristics of flue gas state distribution and its effect on denitrification effect of 220MW coal-fired boiler were studied numerically. At the same time, the optimization scheme of atomization particle size and injection amount of reductant is discussed. The results show that the optimum average particle size of droplet varies with the height in order to ensure sufficient reaction time in the temperature window. Due to the swirling effect of the flue gas injected into the region by reducing agent, the reducing agent is "enriched" locally with the flue gas into the furnace, which leads to the uneven distribution of NH_3/NO at the outlet. The optimization strategy of spray gun atomization parameters: 1 is put forward. The spray gun flow distribution in different regions is adjusted according to the swirl characteristics under the fixed ammonia / nitrogen molar ratio. The simulation results show that: 1. When the ratio of ammonia to nitrogen remains 1.2, compared with the standard operating conditions of the power station, the optimized scheme can increase the denitrification rate from 36.8% to 42.1, and reduce the amount of ammonia leakage by 49 percent. In addition, with the increase of the mole ratio of ammonia to nitrogen, the optimized scheme shows a better denitrification effect. But the degree of optimization is slightly reduced.
【作者单位】：东南大学能源热转换及其过程测控教育部重点实验室;南京龙源环保有限公司;
【基金】：江苏省科技成果转化专项资金项目(BA2015083)
【分类号】：X773

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