Evaluation of Compressor Washing Methods on the Performance Enhancement of Gas Turbine Engines

Authors : Enyia, D. J.

Volume/Issue : Volume 8 - 2023, Issue 8 - August

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/y65sfab2

DOI : https://doi.org/10.5281/zenodo.8285922

Industrial Gas Turbines are subjected to a very harsh operating condition mostly in the oil and gas sector and in the desert environment, thereby causing fouling in the engine component parts, especially the compressor, and the total performance is hence distorted as a result of this degraded engine component. Fouling of the compressor blade is considered in this research. As such, an optimization model for power augmentation was improvised via compressor washing methods. These state-of-the-art washing methods comprises of the online, offline and combination of both methods. This was done to ascertain the most crucial methods to be adopted for further application and advice to gas turbine owners and operators. Here, the operator has the option to select his desired duration for the compressor to be washed between certain intervals while also considering the environment that engine is being operated. The enhancement applied in the work is a computer based linear programming model that is robust and have the ability to investigate the highest and lowest values of the net profit of the project to be determined. Pythia and Turbomatch software of Cranfield University was used for the engine performance simulation, and the outcome appears very accurate since the deviations from existing results do not have much disparity when compared. As such, the engine was validated and hence utilized for the entire research. An investigation of online, offline and a combination of both online and offline compressor washing was evaluated to determine the most economically viable washing method to be implemented to help operators combat the fouling issues and yield profit.

Keywords : Compressor Washing, Efficiency, Fouling, Gas Turbine, Performance.


Paper Submission Last Date
31 - December - 2023

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