摘要
充分挖掘现有机组运行DCS历史数据,直接为优化运行服务,是智能发电技术研发的重要途径。本文以一台600 MW机组近一年DCS存储的相关历史运行数据为基础,分析锅炉运行性能和参数随锅炉出力(主蒸汽流量)和气温(送风机入口风温)的变化。计算分析结果表明:该机组在气温高于年平均值的秋夏季节,相同负荷下的总燃料量比冬春季节明显升高;氮氧化物排放随气温变化不大。秋夏季节负荷较高的情况下,烟气氧量处于合适的水平,风煤配比恰当,但锅炉排烟温度较高,消耗燃料较多,对应锅炉热损失较大。因此,单纯地以追求最佳烟气氧量水平就以为达到了优化燃烧工况的认识和实践是片面的。气温较高的秋夏季节,总风量实际值与理论空气量之差与总燃料量之间显示了良好的正相关性,可能说明总风量高于理想风量是造成秋夏季节燃料量偏大的直接原因之一。
For the research and development of smart power generation technology,it is an important way to fully mine the historical operation data in DCS of existing unit for the optimization of the unit and boiler operation.Based on the relevant historical operation data in the past one year stored in DCS of a 600 MW unit,the boiler operation performance and its parameters varied with its load(main steam flow rate)and air temperature was analyzed.The results show that,when the air temperature in autumn and summer is higher than the annual average,the total fuel consumption under the same load is significantly higher than that in winter and spring,and the NOx emission from the furnace changes little.For higher load level in autumn and summer,the oxygen content of flue gas is at a proper level and then the ratio of air and coal is appropriate,but the temperature of flue gas is high,and the boiler consumes more fuel,which corresponds to a large heat loss of the boiler.Therefore,it is one-sided that the optimal combustion condition can be achieved by simply pursuing the optimal oxygen level of flue gas.In autumn and summer when the air temperature is high,the difference between the actual and theoretical values of total air flow rate shows a good positive correlation with the total fuel consumption,indicating that the deviation of the total air flow rate from the theoretical one maybe one of the direct reasons for the large fuel consumption in autumn and summer.
作者
沈赫男
王承亮
王志
周怀春
SHEN He-nan;WANG Cheng-liang;WANG Zhi;ZHOU Huai-chun(Huadian Weifang Power Generation Co., Ltd., Weifang 261000, China;Huadian International Technical Service Branch, Jinan 250000, China;Research and Development Center of Smart Power Generation Technology, Northeast Electric Power University, Jilin 132012, China)
出处
《节能技术》
CAS
2020年第6期521-526,共6页
Energy Conservation Technology
基金
国家重点研发计划项目(2017YFB0601900)。