空气分级与偏转二次风联用对炉膛燃烧特性的影响

发布时间：2019-05-24 07:44

【摘要】：运用CFD软件对某210 MW煤粉锅炉的燃烧过程进行三维数值模拟,采用空气分级燃烧技术,研究不同空气分级深度及偏转二次风对锅炉的燃烧情况及NOx排放的影响,同时引入"敏感性指数",分析了不同空气分级深度下联用偏转二次风前后对锅炉运行的影响程度。结果表明:单独采用空气分级和偏转二次风均能降低NOx排放,二者联用时空气分级起主导作用,NOx排放降低25%~28%;在不同空气分级深度下联用偏二次风措施对炉内燃烧前后影响程度不同,温度场与组分场出现较为相同的影响规律,在一定燃尽风率区间,存在对应(温度、组分)敏感性系数最大的燃尽风率,敏感性指数随燃尽风率的增加呈先增加后减小的变化趋势,即影响程度先增强后减弱;联用偏转二次风改善炉内结渣和高温腐蚀的效果随燃尽风率先增强后减弱,燃尽风率在18%~25%时效果较好,但导致飞灰含碳率显著增加。
[Abstract]:The three-dimensional numerical simulation of the combustion process of a 210 MW pulverized coal boiler is carried out by using CFD software. The effects of different air classification depth and deflection secondary air on the combustion and NOx emission of a 210 MW pulverized coal boiler are studied by using air classification combustion technology. At the same time, the sensitivity index is introduced to analyze the influence of deflection secondary air on boiler operation before and after different air classification depths. The results show that NOx emission can be reduced by air classification and deflection secondary wind alone, and air classification plays a leading role in the combination of air classification and NOx emission reduction by 25% and 28%. Under different air classification depths, the influence of partial secondary air on the combustion in the furnace is different, and the temperature field and the component field have the same influence law, and there is a corresponding (temperature) in a certain range of burnout air rate. When the sensitivity coefficient is the largest, the sensitivity index increases at first and then decreases with the increase of burnout wind rate, that is, the influence degree increases at first and then weakens. The effect of combined deflection secondary air on improving slagging and high temperature corrosion in the furnace decreases with the increase of burnout wind at first, and the effect is better when the burnout air rate is 18% ~ 25%, but the carbon content of fly ash increases significantly.
【作者单位】：上海理工大学能源与动力工程学院;上海发电设备成套设计研究院;
【基金】：国家自然科学基金资助项目(51176126)
【分类号】：TK229.63

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