Comparison between Thermodynamic Model and Neural Network Model Approach

摘要

In this work, two different approaches are proposed and compared for the modelling of steam turbines, an iterative thermodynamic method and a neural network approach. The iterative thermodynamic model is able to predict steam mass flow, pressure, temperature, enthalpy and power on each turbine drum. The NN model can predict the generated mechanical power. Both models have been trained and validated on a massive dataset created through the internal sizing design tool, which contains the turbine geometrical and mechanical data. Further validation tests have been successfully executed by exploiting field data coming from a solar power plant in which a high pressure and a low pressure turbines are installed.