Fault detection in hybrid power systems

In this study, a hybrid power system was created in Matlab / Simulink software environment. In this system, probable fault conditions that may occur in the hybrid power system have been investigated along the line. Virtual disturbances at certain distances in the energy transmission line are simulated and a data base is created by recording the current and voltage signals of these faults in the computer environment. After normalizing this data in the preprocessing phase, it is passed to the digital signal processing stage. The goal in this phase is to obtain distinctive features of current and voltage signals for faults occurring at different points. Starting from 15th km up to 85th km, virtual faults have been created at each km of the three-phase transmission line which has 100 km length. By repeating the experiments, 497 different faults have been created. Fault types, fault resistances and fault inception angles are changed randomly to obtain similar fault occurance conditions as in real life by preparing a matlab program. To obtain distinctive features, 12-level Discrete Wavelet Transform is used. 4 different statistical parameters including entropy, standard deviation, skeewness and kurtosis are computed for detail and approximation coefficients to build final dataset. For training and validation of the dataset, Matlab Regression Learner App is employed and the obtained results are compared with a lot of methods which are used in the literature. The obtained results show that the proposed method can estimate fault locations with rather small error rate.