天然气粗氦分离系统分析与工艺参数优化
Process Parameter Optimization of Rough Helium Separation from Natural Gas System
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- 引用格式:
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周璇,周泽乾,黄勇,李莹珂,蒲黎明.天然气粗氦分离系统分析与工艺参数优化[J].天然气与石油,2019,37(4):0.doi:
Zhou Xuan , Zhou Zeqian , Huang Yong , Li Yingke , Pu Liming.Process Parameter Optimization of Rough Helium Separation from Natural Gas System[J].Natural Gas and Oil,2019,37(4):0.doi:
- DOI:
- 作者:
- 周 璇1 周泽乾2 黄 勇1 李莹珂1 蒲黎明1
Zhou Xuan1 , Zhou Zeqian2 , Huang Yong1 , Li Yingke1 , Pu Liming1
- 作者单位:
- 1. 中国石油工程建设有限公司西南分公司, 2. 国家知识产权局专利局专利审查协作四川中心
1China Petroleum Engineering & Construction Corp.Southwest Company, Chengdu, Sichuan, 610041 , China;2 Patent Examination Cooperation (Sichuan) Center of the Patent Office, CNIPA
- 关键词:
- 分析;粗氦分离;工艺参数优化;敏感度分析
Exergy analysis; Rough helium separation; Process parameter optimization; Sensitivity analysis
- 摘要:
天然气粗氦分离系统是天然气提氦过程中的主要能耗点,如何在保障产品质量的同时降低过程能耗是一个重要研究内容。通过研究提出了一种基于分析的天然气粗氦分离系统工艺参数优化策略:首先基于分析方法对系统中的用能薄弱环节进行了分析;然后以系统损最小为目标,对过程中涉及的关键工艺参数进行优化,在保障氦气产品收率基础上,尽可能降低过程能耗。同时,还提出了基于敏感度分析的关键工艺参数辨识策略来降低优化过程的计算复杂度。研究结果表明,经过优化后,系统的总损降低11.01%,总用能成本降低11.82%,获得了良好的节能降耗效果。该研究可为天然气粗氦分离系统的工艺参数优化及节能措施开发提供一定借鉴。
The rough helium separation system is the main source of energy consumption in the helium extraction from natural gas process.How to reduce the process energy consumption while ensuring the product quality is an important research topic.A process parameter optimization strategy for rough helium separation system based on exergy analysis is proposed to achieve energy consumption reduction.Firstly, the weak energy segments are evaluated based on exergy analysis approach.Then the key parameters are optimized for the minimal exergy loss of the system.Hence, the energy consumption of the system is reduced farthest when the yield of rough helium is still high enough.Besides, a key process parameter identification strategy based on sensitivity analysis is proposed to reduce the computational complexity of the optimization process.The research results show that the total exergy loss of the system is reduced by 11.01%, and the total energy cost is reduced by 11.82% afterprocess parameter optimization, which has achieved good energy saving and consumption reduction effects.
