Nonlinear simulation of the Francis turbine neural network model

• Main Authors: Jiang Chang, Jiang-Sheng Zhong
• Format: Conference Proceeding
• Language: English
• Subjects: Electronic mail; Equations; Feedforward neural networks; Frequency; Machine learning algorithms; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Power system modeling; Turbines
• DOI: 10.1109/ICMLC.2004.1378584

Due to the difficulty in describing the nonlinear characteristic of Francis turbine and the complex simulation of the Francis turbine governing system (FTGS), this paper takes advantage of the powerful nonlinear approximate ability of the feed forward neural network to put up the Francis turbine neural network model (FTNNM). The Levenberg-Marquardt algorithm is used to train the FTNNM which describes the flow characteristic and the efficiency characteristic. The convergence speed of the offline training is fast and the accuracy of the model is high. The nonlinear model FTNNM and other models consist the nonlinear simulation system under the environment of the SIMULINK of MATLAB. The nonlinear simulation under different operating situations can be implemented in the system. The variability of the different inner parameters of the system and the Francis turbine can be attained quickly and truly. It provides a good base for the research of control policy of the Francis turbine governing system (FTGS).