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