| 摘要: |
| 目的 优化调节某L-BOG深冷提氦装置的关键工艺参数。方法 采用Aspen HYSYS建立流程模型，分析精馏塔温度、回流比等参数对能耗及回收效果的影响，并通过Box-Behnken响应面法设计建立交互作用条件组合试验，模拟得出组合参数优化调节数据。结果 模拟结果显示，精馏塔压力对流程的影响极小，而降低温度、增加回流比以及高位塔板进料均提高了氦回收率，响应曲面分析明确了各变量对氦体积分数和冷凝器、再沸器功率影响的显著性排序。经模型优化，设定精馏塔进料温度为?160 ℃，塔顶回流比为0.655，进料位置为5#塔板，装置设备总能耗降低了20.31%，氦回收率提升了0.12个百分点。结论 基于HYSYS模拟联合Box-Behnken响应面法建立的多因素预测回归模型，可为L-BOG深冷提氦装置提供合理的组合参数运行值，显著降低了设备能耗并提高了氦回收率。 |
| 关键词: L-BOG 提氦 深冷工艺 Aspen HYSYS Box-Behnken响应面法 |
| DOI：10.3969/j.issn.1007-3426.2025.02.007 |
| 分类号: |
| 基金项目: |
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| Optimization of L-BOG deep-cooling helium extraction process by Aspen HYSYS coupled with Box-Behnken response surface methodology |
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Yun YOU1, Li YAN1,2, Xiaoming CHENG3, Xinyuan ZHOU1
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1.School of Petroleum and Natural Gas Engineering, Chongqing University of Science and Technology, Chongqing, China;2.No.4 Gas production Plant, Sinopec Southwest Oil & Gas Company, Chengdu, Sichuan, China;3.PetroChina Southwest Oil & Gasfield Company, Chengdu, Sichuan, China
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| Abstract: |
| Objective The aim is to optimize and adjust the key process parameters of an L-BOG deep-cooling helium extraction plant. Method Aspen HYSYS was used to establish a process model to analyze the effects of distillation column temperature, reflux ratio and other parameters on energy consumption and recovery effectiveness, and then the Box-Behnken response surface analysis was used to design and establish a combination of interaction conditions and simulate the optimization and adjustment of the combination of parameters. Result The process simulation reflected that the distillation column pressure had minimal effect on the process, lowering temperature, increasing reflux ratio and at higher tower plate feeding all improved helium recovery, and the response surface analysis determined the significance order of the effect of each variable on helium volume fraction, condenser power and reboiler power. After optimizing model, the distillation tower feed temperature is set to ?160 ℃, the tower top reflux ratio is 0.655, and the feed position is 5# tower plate, the total energy consumption of the plant is reduced by 20.31%, and the helium recovery rate is increased by 0.12 percentage points. Conclusion A multifactor predictive regression model based on HYSYS simulation coupled with Box-Behnken response surface methodology can provide a reasonable combination of parameter operating values for the L-BOG deep-cooling helium extraction plant, and the method can better realize the reduction of energy consumption and the improvement of helium recovery rate. |
| Key words: L-BOG helium extraction deep-cooling process Aspen HYSYS Box-Behnken response surface methodology |
