State Key Laboratory of Clean Energy Utilization,Institute for Thermal Power Engineering,Zhejiang University,Hangzhou
JiaxingResearch Institute,Zhejiang University,Jiaxing
Dongfang Boiler Group Co. Ltd.,Zigong

锅炉燃烧残碳量是反映锅炉燃烧效率的重要指标,预测其数值对锅炉运行调整及设计有着重要意义。依据试验测量的煤颗粒在炉内的运动路径及停留时间开展炉膛出口含碳量预测计算,探究停留时间、炉膛温度、煤种、过量空气系数对煤颗粒残碳量的影响。结果表明,停留时间越长的煤颗粒残碳量越低;床温从800℃升高到900℃,残碳量降低约40%~50%;过量空气系数从1.05增大到1.3,残碳量降低10%~30%;煤种的特性是影响残碳量的关键因素,煤的挥发分含量、固定碳含量、反应活性决定了煤的燃尽。通过与循环流化床锅炉设计方法计算含碳量对比以及实炉试验数据验证,证明煤颗粒残碳量基于运动轨迹方法预测结果的合理性。

The carbon residue is essential for reflecting the combustion efficiency of CFB boiler,the accurate prediction of carbon residuehas significance for CFB operation and design. Based on the trajectory and residence time of particles in the furnace,the carbon content ofcoal particles out of the furnace is calculated. The effects of residence time,furnace temperature,coal rank,and excess air ratio have beeninvestigated. It is found that the coal particle with longer residence time has lower carbon content. When the bed temperature increasesfrom 800 ℃ to 900 ℃,the carbon residue decreases by about 40%−50%. Increasing the excess air ratio from1.05 to 1.3,the carbon residuereduces by 10%−30%. The rank of coal is the key factor to carbon residue. The volatile, fixed carbon content and reactivity of coaldetermine the burnout behavior. By comparing the calculated results by the CFB design method and the experimental data,it is provedthat the prediction of residual carbon based on the trajectory method is reasonable.

国家重点研究计划项目资助(2020YFB0606201)

马张珂,程乐鸣,李立垚,等.基于颗粒示踪的循环流化床锅炉煤燃烧残碳量预测[J].洁净煤技术,2024,30(11):59−65.

MA Zhangke,CHENG Leming,LI Liyao,et al. Carbon residue prediction of coal combustion in circulating fluidized bed boiler based on particle tracer[J].Clean Coal Technology,2024,30(11):59−65.