Modelling the clogging of gas turbine filter houses in heavy-duty power generation systems

Sabah Ahmed Abdul-Wahab, Abubaker Sayed Mohamed Omer, Kaan Yetilmezsoy and Majid Bahramian

Mathematical and Computer Modelling of Dynamical Systems, 2020, vol. 26, issue 2, 119-143

Abstract: A prognostic approach based on a MISO (multiple inputs and single output) fuzzy logic model was introduced to estimate the pressure difference across a gas turbine (GT) filter house in a heavy-duty power generation system. For modelling and simulation of clogging of the GT filter house, nine real-time process variables (ambient temperature, humidity, ambient pressure, GT produced load, inlet guide vane position, airflow rate, wind speed, wind direction and PM10 dust concentration) were fuzzified using a graphical user interface within the framework of an artificial intelligence-based methodology. The results revealed that the proposed fuzzy logic model produced very small deviations and showed a superior predictive performance than the conventional multiple regression methodology, with a very high determination coefficient of 0.974. A complicated dynamic process, such as clogging phenomenonin heavy-duty GT system, was successfully modelled due to high capability of the fuzzy logic-based prognostic approach in capturing the nonlinear interactions.

Date: 2020
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DOI: 10.1080/13873954.2020.1713821

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