Soft Computation of Turbine Inlet Temperature of Gas Turbine Power Plant Using Type-2 Fuzzy Logic Systems

This paper aims to demonstrate application of type-2 fuzzy logic systems (FLS) to predict a critical parameter of gas turbine in a power plant viz., the Turbine Inlet Temperature (TIT). Maintaining higher TIT than allowed severely affects the life of the components whereas operating at lower TIT may cause low efficiency and low load. Nonavailability of TIT, which cannot be measured directly, puts great limitations on efficient gas turbine operation. Accurate estimation of this parameter requires significant computing power and the time required places limitations on the conventional modeling methods for use in real time applications. It is also demonstrated here by way of comparison, that a type-2 FLS is more robust in the presence of noise uncertainties than a type-1 conventional FLS for this application. Results are verified through the practical plant data obtained from an 88 MW gas turbine power plant.

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