基于Aspen Plus的水泥窑协同处置市政污泥烟气排放特性分析及工艺优化

ANALYSIS OF FLUE GAS CHARACTERISTICS AND PROCESS OPTIMIZATION OF CEMENT KILN CO-PROCESSING MUNICIPAL SLUDGE BASED ON ASPEN PLUS

利用Aspen Plus软件建立了水泥窑协同处置市政污泥的工艺模型,定量分析污泥进料量和含水率对日产万吨熟料的生产线中烟气排放规律、分解炉炉温及煤耗的影响。结果表明:含水率60%的污泥,进料量由1 t/h增加至20 t/h,出口烟气中NO、SO_(2)浓度分别由205.5,26.5 mg/m^(3)变化至56.7,26.8 mg/m^(3);进料量10 t/h的污泥,含水率由10%提高至90%,烟气中NO由136.5 mg/m^(3)降低到133.1 mg/m^(3),后又提高至134.6 mg/m^(3),SO_(2)从27.4 mg/m^(3)降低到26.2 mg/m^(3)。以50%含水率为分界线,高含水率污泥会降低分解炉温度并增加煤耗,低含水率污泥情况则相反。结合模拟结果提出,在维持分解炉温度880~905℃条件下,污泥含水率控制在45%~63%,可保证污泥进料量达到20 t/h。该研究结果可为现行工艺优化方向提供参考。

In this study,a simulation model of cement kiln co-processing municipal sludge technology was developed by Aspen Plus.Based on the case that the daily production of clinker was 10000 t/d,the model aimed to analyze the effect of the changes in feed rate and sludge moisture content on flue gas emission law,the calciner's temperature and coal consumption.The results showed that when the moisture content of sludge remained at 60%,and the feed rate of sludge ranged from 1 t/d to 20 t/d,the concentration of NO and SO_(2) in flue gas changed from 205.5 mg/m^(3) and 26.5 mg/m^(3) to 56.7 mg/m^(3) and 26.8 mg/m^(3),respectively.When the feed rate of sludge remained at 10 t/d,and the moisture content of sludge ranged from 10%to 90%,the concentration of NO decreased from 136.5 mg/m^(3) to 133.1 mg/m^(3) and then increased to 134.6 mg/m^(3),while the concentration of SO_(2) decreased from 27.4 mg/m^(3) to 26.2 mg/m^(3).50%was the critical moisture content of sludge for the changes in the calciner's temperature and coal consumption.Higher moisture content decreases the temperature and increases consumption,while the opposite is true for lower moisture content.According to simulation results,it is proposed that by maintaining the calciner temperature within the range of 880~905℃,the moisture content of sludge can be controlled at 45%~63%,thereby ensuring a sludge feed rate of 20 t/h.The optimized production parameters are proposed to provide a reference for current technology optimization.