Abdulhalim Musa Abubakar , Lukman Buba Umdagas , Moses NyoTonglo Arowo , Marwea Al-Hedrewy , Mahlon Kida Marvin , Noureddine Elboughdiri , Aminullah Zakariyya Abdul , Jenisus O. Dejarlo , Rezkallah Chafika
{"title":"模拟从湿天然气中同时回收二氧化碳和甜碳中性天然气的系统:对工艺输入和装置性能的深入研究","authors":"Abdulhalim Musa Abubakar , Lukman Buba Umdagas , Moses NyoTonglo Arowo , Marwea Al-Hedrewy , Mahlon Kida Marvin , Noureddine Elboughdiri , Aminullah Zakariyya Abdul , Jenisus O. Dejarlo , Rezkallah Chafika","doi":"10.1016/j.cles.2024.100156","DOIUrl":null,"url":null,"abstract":"<div><div>The growing need for carbon-neutral energy solutions necessitates the development of efficient systems for carbon dioxide (CO<sub>2</sub>) recovery and the production of sweet carbon-neutral natural gas (CNNG) from wet natural gas. Despite existing approaches, limitations in process optimization, solvent efficiency, and output purity persist. This study aims to address these gaps by simulating a system for simultaneous recovery of CO<sub>2</sub> and CNNG using an integrated three-stage process, modeled in Aspen Plus V8.8. 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引用次数: 0
摘要
由于对碳中性能源解决方案的需求日益增长,因此有必要开发二氧化碳(CO2)回收和从湿天然气中生产甜碳中性天然气(CNNG)的高效系统。尽管已有一些方法,但在工艺优化、溶剂效率和产出纯度方面仍存在局限性。本研究旨在利用 Aspen Plus V8.8 中建模的集成式三阶段工艺模拟同时回收 CO2 和 CNNG 的系统,从而弥补这些不足。这项工作的独特之处在于采用 ENRTL-RK 基础模型,并结合敏感性分析来优化 13 个相互连接的工艺单元(包括压缩机、热交换器和萃取塔)的输入参数。主要创新包括采用新颖的装置配置,在最佳条件下,CNNG 的回收效率达到 95.94%,二氧化碳纯度达到 93.185%,超过了传统方法。通过仔细调整输入参数,提高了单乙醇胺(MEA)溶剂的性能,与标准操作设置相比,其吸收效率提高了 12%。敏感性分析表明,进料压力和溶剂流速等关键参数是最大化产出效率的主要驱动因素。这项研究还对动力需求进行了详细的量化评估,在 110 巴排气压力下,压缩机制动马力 (BHP) 为 182605 瓦。通过引入系统的工艺优化方法,该研究填补了现有的研究空白,显著提高了 CNNG 和 CO2 的纯度和回收率,同时最大限度地降低了能耗。研究结果不仅证明了该工艺的可行性,还为进一步完善可持续气体处理技术奠定了基础。
Simulation of a system to simultaneously recover CO2 and sweet carbon-neutral natural gas from wet natural gas: A delve into process inputs and units performances
The growing need for carbon-neutral energy solutions necessitates the development of efficient systems for carbon dioxide (CO2) recovery and the production of sweet carbon-neutral natural gas (CNNG) from wet natural gas. Despite existing approaches, limitations in process optimization, solvent efficiency, and output purity persist. This study aims to address these gaps by simulating a system for simultaneous recovery of CO2 and CNNG using an integrated three-stage process, modeled in Aspen Plus V8.8. The unique aspect of this work lies in employing the ENRTL-RK base model, coupled with sensitivity analyses to optimize input parameters across 13 interconnected process units, including compressors, heat exchangers, and extraction columns. Key innovations include the novel configuration of units, yielding a recovery efficiency of 95.94% for CNNG and a CO2 purity of 93.185% at optimal conditions, surpassing conventional methods. The performance of the monoethanolamine (MEA) solvent was enhanced by careful adjustment of input parameters, improving its absorption efficiency by 12% compared to standard operational settings. Sensitivity analysis revealed critical parameters such as feed pressure and solvent flow rate as primary drivers for maximizing output efficiency. This study also provides a detailed quantitative assessment of power requirements, with a compressor brake horsepower (BHP) of 18,2605 watts at 110 bar discharge pressure. It addresses the existing research gap by introducing a systematic approach to process optimization, significantly improving the purity and recovery of CNNG and CO2 while minimizing energy consumption. The results not only demonstrate the viability of this process but also provide a foundation for further refinement in sustainable gas processing technologies.