The continuous monitoring of gas turbines in commercial power plant operation provides long-term engine data of field units. Evaluation of the engine performance is challenging as, apart from variations of operating points and environmental conditions, the state of the engine is subject to changes due to the ageing of engine components. The measurement devices applied to the unit influence the analysis by means of their accuracy, which may itself alter with time. Furthermore, the available measurements do usually not cover all necessary information for the evaluation of the engine performance. To overcome these issues, this paper describes a method to systematically evaluate long term operation data without the incorporation of engine design models since the latter do not cover performance changes when components are ageing. Key focus of the methodology thereby is to assess long-term emission performance in the most reliable manner.
The analysis applies a data reconciliation method to long-term operating data in order to model the engine performance including non-measured variables and to account for measurement inaccuracies. This procedure relies on redundancies in the data set due to available measurements and the identification of suitable additional constituting equations that are independent of component ageing. The resulting over-determined set of equations allows for performing a data set optimization with respect to a minimal cumulated deviation to the measurement values, which represents the most probable, real state of the engine. The paper illustrates the development and application of the method to analyse the gas path of a commercial gas turbine in a combined cycle power plant with long-term operating data.