Published Paper Details:

The quality of electric power and disturbances occurred in power signal has become a major issue among the electric power suppliers and customers. The power quality disturbances caused by large-scale grid connection of nonlinear loads and distributed generations seriously affect the safe and stable operation of precision computers and microprocessors in the power grid, and may cause serious security accidents and economic losses in some cases. Therefore, the accurate classification of power quality disturbances is of great significance for the power supply quality improvement. Most of the disturbances are non-stationary and transitory in nature hence it requires advanced tools and techniques for the analysis of PQ disturbances. This project work presents an algorithm based on the Hilbert Transform for the classification of single multiple and multistage power quality disturbances. These power quality disturbances signals are generated using the simulation models and integral mathematical models of PQ disturbances using the MATLAB Environment. The single Power quality disturbances considered in this study are voltage sag, voltage swell, voltage interruption, the multiple power quality disturbances considered in the study are voltage sag with harmonics, voltage swell with harmonics, voltage interruption with harmonics and the multistage power quality disturbances considered in the study are multistage voltage sag, multistage voltage swell, multistage voltage sag with swell. These signals are processed using the Hilbert transform to obtain the power quality index curve and extract features from it. Multiple cases of power quality disturbances are created by varying the parameters and a dataset is created. A feature vector is created by processing the dataset signals using Hilbert transform in order to train and test the ANN classifier. The effectiveness of the proposed approach is obtained by calculating the efficiency of proposed algorithm. A thresholding based approach is also used to classify the single, multiple and multistage power quality disturbances.