摘要
以氨法烟气脱硫原理及非平衡级传质模型为基础,利用Aspen Plus模拟系统对某合成氨厂氨法烟气脱硫工艺过程进行建模与数值模拟研究。通过对模拟结果的分析得出:现有工艺流程存在不足,即不能很好地满足脱硫要求,且提高脱硫率会增大生产操作费用。因此,在现有工艺流程基础上提出了"AN1+AN2"的补氨工艺优化方案,并对优化方案进行模拟计算与分析。模拟结果表明,最优的补氨位置为:AN1的补氨位置在SO2吸收段一级喷淋段和二级喷淋段的中间;AN2的补氨位置在氧化段底部,通过现有工艺的氧化空气管道利用氧化空气吹扫进入氧化段;同时,补氨方式可以采取自动变频控制系统来实现。优化后,烟气脱硫率为95%,出口净烟气中SO2质量浓度为411 mg/m3,NH3质量浓度为17.5 mg/m3,各工艺指标基本能够满足正常生产要求。
The model of SO2 removal process in the packing absorption tower of a synthetic ammonia plant was established and analyzed by the chemical process simulation software Aspen Plus based on ammonia-based flue gas desulfurization theory and none-equilibrium mass transfer model. Through the analysis of simulation results, the existing process is not good enough to meet the desulfurization requirement, and the increasing of desulfurization rate is at the cost of ammonia waste and the secondary pollution, so the existing process needs to be modified and optimized. The complement ammonia optimization scheme named ＂ AN1 ＋ AN2＂ was put forward and the optimization module tool of Aspen Plus was used to optimize and analyze the retrofit scheme. The optimization simulation results reveal that AN1 complement ammonia position is in the middle of first spray section and secondary spray section of SO2 absorption segment; AN2 complement ammonia position is in the bottom of oxidation segment, through the oxidation air pipe using oxidation air purge into oxidation segment. At the same time, the automatic frequency conversion control system can be realized by using complement ammonia method. The desulfurization efficiency is 95% and SO2 export mass concentration is 411 mg/m3 and NH3 export mass concentration is 17.5 mg/ m3 in flue gas after optimization. Each technological index is in the controlled range and meets the requirements of normal production.
出处
《化学工程》
CAS
CSCD
北大核心
2014年第4期7-12,共6页
Chemical Engineering(China)
基金
国家863支撑项目(2011AA060803)
贵州省绿色化工技术科技创新人才团队(黔科合人才团队[2009]4002)
贵州大学研究生创新基金项目(研理工2014046)
关键词
氨法
烟气脱硫
ASPEN
PLUS
模拟
工艺优化
ammonia-based method
flue gas desulfurization
Aspen Plus
simulation
process optimization
