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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Nurlan Batayev
Satbayev University
Computer Science & IT Electrical & Electronics Engineering

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Centrifugal compressor anti-surge control system modelling Nurlan Batayev; Batyrbek Suleimenov; Sagira Batayeva
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp1419-1428

Abstract

From the middle of XX century, natural gas is an important mineral, widely used in the energy sector. Transportation of natural gas is carried out via gas pipeline networks and compression stations. One of the key features which need to be implemented for any centrifugal gas compressor is a surge protection. This article describes the method and develops software application intended for simulation and study of surge protection system of a centrifugal compressor used in modern gas compression stations. Within the article research method, modelling environment’s block diagram, proposed algorithms and results are described. For surge cases control and prediction, Anti-surge control block implemented which based on practical experience and centrifugal compressor theory. To avoid complicated energy balancing differential equations the volumetric flow calculation algorithm proposed which is used in combination with Redlich-Kwong equation of state. Developed software’s adequacy test performed through modeling of one-stage gas compression scheme at rated speed with comparison of parameters with reference commercial software and verification of the anti-surge control system.
Axial compressor fouling detection for gas turbine driven gas compression unit Nurlan Batayev
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1257-1263

Abstract

One of the main reasons of the performance degradation of gas turbines is the axial compressor fouling due to air pollutants. Considering the fact that the fouling leads to high consumption of fuel, reducing of the axial compressor’s discharge air pressure and increasing of the exhaust temperature, thus designing a compressor degradation detection system will allow prevent such issues. Many gas turbine plants lose power due to dirty axial compressor blades, which can add up to 4% loss of power. In case of power plants, the power loosing could be observed by less megawatts produced by generator. But in case of gas compression stations the effect of power loosing could not be quickly detected, because there is not direct measurement of the discharge power produced by gas turbine. This article represents technique for detection of gas turbine axial compressor degradation in case of gas turbine driven natural gas compression units. Calculation of the centrifugal gas compressor power performed using proven methodology. Approach for evaluation of the gas turbine performance based on machine learning prediction model is shown.  Adequacy of the model has been made to three weeks’ operation data of the 10 Megawatt class industrial gas turbine.
Co-Authors Batyrbek Suleimenov Sagira Batayeva