4.5 Article Proceedings Paper

On-line combustion monitoring on dry low NOx industrial gas turbines

Journal

MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 14, Issue 7, Pages 1123-1130

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/0957-0233/14/7/330

Keywords

on-line monitoring; combustion; instabilities; gas turbine; NOx

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To reduce the NO., emissions levels produced by industrial gas turbines most manufacturers have adopted a lean premixed approach to combustion. Such combustion systems are susceptible to combustion-driven oscillations, and much of the installed modem gas turbines continue to suffer from reduced reliability due to instability-related problems. The market conditions which now exist under the New Electricity Trading Arrangements provide a strong driver for power producers to improve the reliability and availability of their generating units. With respect to low-emission gas turbines, such improvements can best be achieved through a combination of sophisticated monitoring, combustion optimization and, where appropriate, plant modifications to reduce component failure rates. On-line combustion monitoring (OLCM) provides a vital contribution to each of these by providing the operator with increased confidence in the health of the combustion system and also by warning of the onset of combustion component deterioration which could cause significant downstream damage. The OLCM systems installed on Powergen's combined cycle gas turbine plant utilize high-temperature dynamic pressure transducers mounted close to the combustor to enable measurement of the fluctuating pressures experienced within the combustion system. Following overhaul, a reference data set is determined over a range of operating conditions. Real-time averaged frequency spectra are then compared to the reference data set to enable identification of abnormalities. Variations in the signal may occur due to changes in ambient conditions, fuel composition, operating conditions, and the onset of component damage. The systems on Powergen's plant have been used successfully to detect each of the above, examples of which are presented here.

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