Gas turbine gas path diagnosis under transient operating conditions: A steady state performance model based local optimization approach

Abstract

To improve gas turbine reliability and availability and prolong service life while reducing operation and maintenance costs, many gas path diagnostic methods based on steady state or quasi-steady state have been obtained, but no complete scientific system of gas-path diagnosis has been formed yet. Nowadays the operation of gas turbines needs to be more flexible in grid support mode, and the service life will be consumed faster than that during base load steady-state /quasi-steady-state operation under transient conditions. Therefore, it is urgent to solve the problem of optimal identification of component health parameters under transient conditions. Aiming at above problem, a novel gas path diagnostic method is proposed. Firstly, an equivalent cooling flow processing method is proposed for thermodynamic modeling for gas path diagnostic purpose. Secondly, a steady state performance model based diagnostic scheme under transient conditions based on local optimization algorithm is proposed. At last the diagnostic performance with Newton-Raphson algorithm and Kalman filter algorithm as local optimization algorithm is comparatively analyzed. The case studies have showed that the proposed diagnostic method can be effectively utilized to detect both component gradual failure and abrupt fault quantitatively and the former has better real-time performance and diagnostic accuracy under transient conditions.