Performance Prediction of A Power Generation Gas Turbine Using An Optimized Artificial Neural Network Model (AIUB Journal of Science and Engineering (AJSE), 2024)
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.‎
Keywords: Artificial neural network, gas turbine, performance prediction, ‎system modelling‎