1. 厦门理工学院 机械与汽车工程学院,福建,厦门,361024
2. 福建省绿色智能清洗技术与装备重点实验室,福建,厦门,361024
[ "夏宁(1999—),男,江西九江人,硕士研究生,研究方向为碳捕集工艺优化" ]
[ "何堤(通信作者),男,讲师,博士,E-mail:hed20@xmut.edu.cn" ]
网络出版:2025-09-16,
纸质出版:2025
移动端阅览
夏宁,何堤,陈水宣,洪昭斌,辜佳鑫. 醇胺法CO2捕集双塔耦合工艺及参数优化动力工程学报, 2025, 45(9): 1527-1535 https://doi.
org/10.19805/j.cnki.jcspe.2025.240484
夏宁,何堤,陈水宣,洪昭斌,辜佳鑫. 醇胺法CO2捕集双塔耦合工艺及参数优化动力工程学报, 2025, 45(9): 1527-1535 https://doi. DOI: 10.19805/j.cnki.jcspe.2025.240484.
org/10.19805/j.cnki.jcspe.2025.240484 DOI:
为解决现有化学吸收法碳捕集设备再生能耗较高、体积庞大不利于撬装化设计等问题
提出了一种双塔乙醇胺(MEA)溶液吸收CO
2
方案
结合塔间烟气冷却工艺、富液分流工艺与热泵工艺
以降低塔高和再生能耗
同时提高捕集效率。通过Aspen Plus与Matlab软件的交互仿真模拟
采用粒子群算法对双塔耦合工艺的贫液负荷、塔间烟气冷却温度、贫液分流比、冷富液分流比等参数进行了全局优化。结果表明:优化后得到最佳操作条件为贫液负荷0.291 mol/mol
塔间烟气冷却温度40 ℃
贫液分流比0.577
冷富液分流比0.2;各节能工艺耦合后能有效降低再生能耗
在最优操作条件下
CO
2
捕集率可达到93.27%
综合优化后的再生能耗可降至2.924 GJ/t
较传统工艺节能30.87%。
A dual-tower monoethanolamine (MEA) solution CO
2
absorption scheme was proposed to solve the problems of high regeneration energy consumption and large equipment size of existing chemical absorption carbon capture systems
which was unfavorable for skid-mounted design. The scheme combined inter-tower gas cooling
rich solution split-stream
and heat pump process to reduce tower height and regeneration energy consumption while enhancing capture efficiency. Through interactive simulation using Aspen Plus and Matlab software
the particle swarm optimization algorithm was applied for global optimization of dual-tower coupling parameters
including lean solution loading
inter-tower gas cooling t
emperature
lean solution split ratio
and cold rich solution split ratio. Results show that the optimal operating conditions obtained after optimization are 0.291 mol/mol of lean liquid load
40 ℃ of flue gas cooling temperature between towers
0.577 of lean liquid diversion ratio
and 0.2 of cold-rich liquid diversion ratio. Coupling various energy-saving processes can significantly reduce the regeneration energy consumption. Under the optimal operating conditions
CO
2
capture rate can reach 93.27%
and the comprehensive optimized regeneration energy consumption can be reduced to 2.924 GJ/t
saving 30.87% energy compared with traditional processes.
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