| 摘要: |
| 目的 针对天然气净化厂处理含硫天然气时常出现能耗较高、净化气流量较低、脱硫选择性较差等问题，基于Aspen HYSYS流程模拟软件，搭建含硫天然气净化厂脱硫单元稳态模拟模型。方法 采用多目标正交试验法与综合频率分析法相结合的方法，以工艺总能耗、净化气流量和选择因子3个指标作为综合评判指标，对脱硫单元的吸收塔塔板数、吸收塔压力、胺液循环量和胺液进料温度4个关键工艺参数进行了优化，确定了脱硫单元工艺参数的最优组合方案，并对优化前后脱硫单元的综合性能进行了对比分析。结果 ①所搭建的稳态模拟模型能够准确地模拟脱硫单元的运行特性，满足工程应用的要求；②各因素对工艺总能耗的影响从大到小依次为：胺液循环量、吸收塔塔板数、吸收塔压力和胺液进料温度；各因素对净化气流量和选择因子的影响从大到小的顺序一致，均为吸收塔塔板数、吸收塔压力、胺液循环量和胺液进料温度；③脱硫单元关键工艺参数的最优组合为：吸收塔塔板数12块、吸收塔压力5.5 MPa、胺液循环量75 t/h、胺液进料温度28 ℃；④相较于优化前，优化后的工艺总能耗由11 316.54 kW降至9 590.61 kW，降幅为15.25%；净化气流量由4 164.53 kmol/h增至4 175.54 kmol/h，增幅为0.26%；选择因子由1.32增至2.20，增幅为66.67%。结论 经过工艺参数优化后，脱硫单元的能耗显著降低，净化气流量得到一定的提升，脱硫选择性得到明显改善。 |
| 关键词: 天然气脱硫 正交试验 能耗分析 净化气流量 脱硫选择性 工艺优化 |
| DOI：10.3969/j.issn.1007-3426.2024.05.016 |
| 分类号: |
| 基金项目:中国石油西南油气田公司科研项目“天然气净化厂能源管控技术研究”（20230307-07）；中国石油西南油气田公司科研项目“气田典型耗能设备优化级能源管控模型研究”（20220307-09） |
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| Multi-objective optimization of natural gas desulfurization process based on orthogonal test |
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Xiaoyun YIN1,2, Jing LI1,2, Dong LIN1,2, Xinyu HUANG1,2, Xiaoman ZHOU1,2, Xun ZHANG1,2, Mengjie DENG3, Yang LUO4
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1.Safety, Environment and Technology Supervision Research Institute, PetroChina Southwest Oil & Gasfield Company, Chengdu, Sichuan, China;2.Shale Gas Evaluation and Exploitation Key Laboratory of Sichuan Province, Chengdu, Sichuan, China;3.Southern Sichuan Gas District, PetroChina Southwest Oil & Gasfield Company, Luzhou, Sichuan, China;4.Chongqing Gas District, PetroChina Southwest Oil & Gasfield Company, Chongqing, China
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| Abstract: |
| Objective The aim is to solve the problems of high energy consumption, low purified gas flow rate and poor desulfurization selectivity in treating sour gas in natural gas purification plants. Based on Aspen HYSYS process simulation software, a steady-state simulation model of the desulfurization unit in a sour gas purification plant was established. Methods The multi-objective orthogonal test method and the comprehensive frequency analysis method were combined to optimize the four key process parameters of the desulfurization unit, such as the absorption tower tray number, the absorption tower pressure, the amine solution circulation rate and amine solution feed temperature, with the three indexes of the total energy consumption, the flow rate of the purified gas and the selection factor as the comprehensive evaluation indexes. The optimal combination scheme of the desulfurization unit process parameters was determined, and the comprehensive performance of the desulfurization unit before and after optimization was compared and analyzed.Results Firstly, the steady-state simulation model could accurately simulate the desulfurization unit's operation characteristics and meet the engineering application requirements. Secondly, the factors influencing the total process energy consumption ranked in descending order were amine solution circulation rate, absorption tower tray number, absorption tower pressure, and lean amine solution feed temperature; the factors affecting the purified gas flow rate and selection factor are both ranked from top to bottom as absorption tower tray number, absorption tower pressure, amine solution circulation rate, and lean amine solution feed temperature. Thirdly, the optimal combination of the key process parameters for the desulfurization unit was as follows: absorption tower tray number was 12, absorption tower pressure was 5.5 MPa, amine solution circulation rate was 75 t/h, and lean amine solution feed temperature was 28 ℃. Fourthly, after optimization, the total process energy consumption decreased from 11 316.54 kW to 9 590.61 kW, with a drop of 15.25%; the purified gas flow rate increased from 4 164.53 kmol/h to 4 175.54 kmol/h, with a rise of 0.26%; the selection factor increased from 1.32 to 2.20, with a rise of 66.67%. Conclusions Through the optimization of process parameters, the energy consumption of the desulfurization unit is apparently reduced, the purified gas flow rate is improved to some extent, and the desulfurization selectivity is significantly improved. |
| Key words: natural gas desulfurization orthogonal test energy consumption analysis purified gas flow rate desulfurization selectivity process optimization |
