压缩机清洗对石油和天然气应用中输出功率的好处

Enyia James Diwa, D. Igbong, A. Archibong, U. Eyo
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引用次数: 0

摘要

燃气轮机压缩机结垢已被证明是不可避免的,但在线压缩机清洗已被证明有希望减轻结垢的影响。尽管在实验室或实际发动机运行中进行了一些研究和实验,但经济效益始终是非常重要的。本研究旨在给出压缩机最佳在线水洗频率,并确定高压涡轮HPT的蠕变寿命,在本研究中,HPT为一、二级动叶。采用西门子双轴工业燃气轮机(SGT200 Tornado)进行了性能仿真和退化模型。在Turbomatch库中没有Tornado燃气轮机的发动机代码,因为发动机制造商(Siemens, Lincoln, UK)提供的这些数据在设计点上被应用,并且Turbomatch发动机程序使用提供的数据在设计和非设计点上都成功运行。通过了解潜在的积垢机理,以及使用Pythia软件和具有可测量参数的非线性气路分析应用设计点数据的可能性,对发动机模型进行了恶化。采用Larson-Miller参数LMP方法研究了提高汽轮机入口温度TET对大功率汽轮机高温蠕变寿命的影响。因此,确定了压缩机洗涤优化,并发现最佳在线压缩机洗涤间隔为每四天一次。对电力价格、停机成本、燃料价格和降解率进行了敏感性分析,并给出了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benefit of Compressor Washing on Power Output in Oil and Gas Applications
Fouling in gas turbine compressor has proven to be inevitable, but online compressor washing has shown to be promising in mitigating the effects of fouling. Despite the several researches and experiments carried out in laboratories or actual engine operations as presented in literatures, the economic benefit is always very important. This research aim to present the optimum online compressor water washes frequency and determines the creep life of the high pressure turbine HPT, which in this case is the first and second stage of the rotor blades. A Siemens twin shaft industrial gas turbine (SGT200 Tornado) was used for the performance simulation and degradation model. The engine code for Tornado gas turbine was not available in the Turbomatch library, as such data provided by engine manufacturer (Siemens, Lincoln, UK), was applied at the design point and the Turbomatch engine program ran successfully for both design and off-design point with the supplied data. The engine model was deteriorated with knowledge of underlying fouling mechanism and the possibility to apply the design point data using Pythia software and the non-linear gas path analysis with measurable parameters. Larson-Miller parameter LMP approach was applied in determining the effect of increasing turbine entry temperature TET on high power turbine HPT creep life. Hence, the compressor wash optimisation was determined, and the optimum online compressor wash interval was found to be once in every four days. The sensitivity analysis for the price of electricity, shutdown cost, fuel price, and degradation rate was tested, and the results are presented.
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