Performance Prediction of A Power Generation Gas Turbine Using An Optimized Artificial Neural Network Model

This paper presents the application of an Artificial Neural Network (ANN) based model for performance ‎prediction of a power generation gas turbine. The suggested model was optimized to provide a large ‎database for comparison between different ANN topologies. Then, based on the optimization results, the ‎Multi-Layer Perceptron (MLP) of two layers was constructed and utilized for this study as the best-‎optimized topology. Training of this model was done using historical operational data of a Rolls Royce ‎‎(RB21-24G) gas turbine unit. The outcome results from this model used for performance prediction show ‎good accuracy for different ambient conditions and variable power ratings. Then, a degradation study was ‎also introduced comparing measurements of the same gas turbine utilizing one year later, on-site ‎operational data, with the predicted values generated by the ANN model. The result shows consistency ‎between the measured data and the model results.‎