摘要
为了降低联产LNG天然气低温提氦工艺的综合能耗,提高联产工艺的经济性。本文以四川某天然气提氦厂为例,利用HYSYS软件对联产LNG天然气低温提氦工艺进行模拟,通过对设备能耗进行分析确立影响工艺综合能耗的关键参数,并通过单因素分析得到各参数的取值范围,粗氦浓度为63.5%以上的基础上以综合能耗最低为优化目标构建优化函数模型,并利用遗传算法求解所构建的优化函数模型,由此求得最佳参数组合。得到的最佳参数组合为:一级提氦塔进料温度为-116.6℃,一级提氦塔进料压力为2.84 MPa,一级提氦塔回流比为1.2,氮气制冷剂高压压力为7 MPa,氮气制冷剂低压压力为340 kPa,氮气制冷剂流量为4 000 kmol/h,系统总能耗降低了10.46%,有显著的节能效果。
In order to reduce the comprehensive energy consumption of the combined production LNG natural gas low-temperature helium extraction process and enhance the economic viability of the combined production process,a simulation of the combined production LNG natural gas low-temperature helium extraction process was conducted using HYSYS software,taking a helium extraction plant in Sichuan as an llustrative example.The analysis of equipment energy consumption was carried out to identify the key parameters influencing the overall process energy consumption.By means of single-factor analysis,the value ranges of these parameters were determined.With a focus on minimizing overall energy consumption while maintaining a crude helium concentration above 63.5%,an optimization function model was constructed.Subsequently,a genetic algorithm was employed to solve the optimization function model,yielding the optimal parameter combination.The obtained optimal parameter combination comprises an inlet temperature of-116.6℃ for the first-stage helium extraction tower,an inlet pressure of 2.84 MPa for the first-stage helium extraction tower,a reflux ratio of 1.2 for the first-stage helium extraction tower,a high-pressure pressure of 7 MPa for the nitrogen refrigerant,a low-pressure pressure of 340 kPa for the nitrogen refrigerant,and a flow rate of 4000 kmol/h for the nitrogen refrigerant.A reduction of 10.46%in total system energy consumption was achieved,demonstrating a significant energy-saving effect.
作者
肖荣鸽
庞琳楠
刘亚龙
Xiao Rongge;Pang Linnan;Liu Yalong(Key Laboratory of Special Production Enhancement Technology for Oil and Gas Fields of Shaanxi Province,School of Petroleum Engineering,Xian Shiyou University,Xian 710065,China)
出处
《低温与超导》
CAS
北大核心
2023年第10期47-53,60,共8页
Cryogenics and Superconductivity
基金
西安市科技计划高校人才服务企业项目(22GXFW0106)资助。
关键词
提氦
低温
氮气循环制冷
HYSYS模拟
遗传算法
参数优化
Helium extraction
Low temperatures
Nitrogen circulating refrigeration
HYSYS simulation
Genetic algorithm
Parameter optimization