A dynamic prognosis scheme for flexible operation of gas turbines

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A dynamic prognosis scheme for flexible operation of gas turbines. / Tsoutsanis, Elias; Meskin, Nader; Benammar, Mohieddine; Khorasani, Khashayar.

In: Applied Energy, Vol. 164, 15.02.2016, p. 686-701.

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Tsoutsanis, Elias ; Meskin, Nader ; Benammar, Mohieddine ; Khorasani, Khashayar. / A dynamic prognosis scheme for flexible operation of gas turbines. In: Applied Energy. 2016 ; Vol. 164. pp. 686-701.

Bibtex

@article{88ca2d4928434bfeadbe9e32fcd3636f,
title = "A dynamic prognosis scheme for flexible operation of gas turbines",
abstract = "The increase in energy demand has led to expansion of renewable energy sources and their integration into a more diverse energy mix. Consequently the operation of thermal power plants, which are spearheaded by the gas turbine technology, has been affected. Gas turbines are now required to operate more flexible in grid supporting modes that include part-load and transient operations. Therefore, condition based maintenance should encapsulate this recent shift in the gas turbine's role by taking into account dynamic operating conditions for diagnostic and prognostic purposes. In this paper, a novel scheme for performance-based prognostics of industrial gas turbines operating under dynamic conditions is proposed and developed. The concept of performance adaptation is introduced and implemented through a dynamic engine model that is developed in Matlab/Simulink environment for diagnosing and prognosing the health of gas turbine components. Our proposed scheme is tested under variable ambient conditions corresponding to dynamic operational modes of the gas turbine for estimating and predicting multiple component degradations. The diagnosis task developed is based on an adaptive method and is performed in a sliding window-based manner. A regression-based method is then implemented to locally represent the diagnostic information for subsequently forecasting the performance behavior of the engine. The accuracy of the proposed prognosis scheme is evaluated through the Probability Density Function (PDF) and the Remaining Useful Life (RUL) metrics. The results demonstrate a promising prospect of our proposed methodology for detecting and predicting accurately and efficiently the performance of gas turbine components as they degrade over time.",
keywords = "Adaptive methods, Diagnostics, Gas turbine, Operational flexibility, Prognostics",
author = "Elias Tsoutsanis and Nader Meskin and Mohieddine Benammar and Khashayar Khorasani",
year = "2016",
month = feb,
day = "15",
doi = "10.1016/j.apenergy.2015.11.104",
language = "English",
volume = "164",
pages = "686--701",
journal = "Applied Energy",
issn = "0306-2619",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - A dynamic prognosis scheme for flexible operation of gas turbines

AU - Tsoutsanis, Elias

AU - Meskin, Nader

AU - Benammar, Mohieddine

AU - Khorasani, Khashayar

PY - 2016/2/15

Y1 - 2016/2/15

N2 - The increase in energy demand has led to expansion of renewable energy sources and their integration into a more diverse energy mix. Consequently the operation of thermal power plants, which are spearheaded by the gas turbine technology, has been affected. Gas turbines are now required to operate more flexible in grid supporting modes that include part-load and transient operations. Therefore, condition based maintenance should encapsulate this recent shift in the gas turbine's role by taking into account dynamic operating conditions for diagnostic and prognostic purposes. In this paper, a novel scheme for performance-based prognostics of industrial gas turbines operating under dynamic conditions is proposed and developed. The concept of performance adaptation is introduced and implemented through a dynamic engine model that is developed in Matlab/Simulink environment for diagnosing and prognosing the health of gas turbine components. Our proposed scheme is tested under variable ambient conditions corresponding to dynamic operational modes of the gas turbine for estimating and predicting multiple component degradations. The diagnosis task developed is based on an adaptive method and is performed in a sliding window-based manner. A regression-based method is then implemented to locally represent the diagnostic information for subsequently forecasting the performance behavior of the engine. The accuracy of the proposed prognosis scheme is evaluated through the Probability Density Function (PDF) and the Remaining Useful Life (RUL) metrics. The results demonstrate a promising prospect of our proposed methodology for detecting and predicting accurately and efficiently the performance of gas turbine components as they degrade over time.

AB - The increase in energy demand has led to expansion of renewable energy sources and their integration into a more diverse energy mix. Consequently the operation of thermal power plants, which are spearheaded by the gas turbine technology, has been affected. Gas turbines are now required to operate more flexible in grid supporting modes that include part-load and transient operations. Therefore, condition based maintenance should encapsulate this recent shift in the gas turbine's role by taking into account dynamic operating conditions for diagnostic and prognostic purposes. In this paper, a novel scheme for performance-based prognostics of industrial gas turbines operating under dynamic conditions is proposed and developed. The concept of performance adaptation is introduced and implemented through a dynamic engine model that is developed in Matlab/Simulink environment for diagnosing and prognosing the health of gas turbine components. Our proposed scheme is tested under variable ambient conditions corresponding to dynamic operational modes of the gas turbine for estimating and predicting multiple component degradations. The diagnosis task developed is based on an adaptive method and is performed in a sliding window-based manner. A regression-based method is then implemented to locally represent the diagnostic information for subsequently forecasting the performance behavior of the engine. The accuracy of the proposed prognosis scheme is evaluated through the Probability Density Function (PDF) and the Remaining Useful Life (RUL) metrics. The results demonstrate a promising prospect of our proposed methodology for detecting and predicting accurately and efficiently the performance of gas turbine components as they degrade over time.

KW - Adaptive methods

KW - Diagnostics

KW - Gas turbine

KW - Operational flexibility

KW - Prognostics

UR - http://www.scopus.com/inward/record.url?scp=84950973360&partnerID=8YFLogxK

U2 - 10.1016/j.apenergy.2015.11.104

DO - 10.1016/j.apenergy.2015.11.104

M3 - Article

AN - SCOPUS:84950973360

VL - 164

SP - 686

EP - 701

JO - Applied Energy

JF - Applied Energy

SN - 0306-2619

ER -