Research Of Power Quality Disturbances' Detection And Classification

With development and popularization of high technology industry such as computer, power electronics and information technology, power quality disturbance attacts more and more attention from power suppliers and power clients. In order to reduce influence caused by power quality problems, the thesis centers on problems such as power qualtity disturbances' detection and classification and de-noising of power quality disturbance signals and verifies effectives of proposed algorithms by simulation.In order to detect and classify power quality disturbances, algorithm based on grand-S transform and na(?)ve Bayes is proposed. Power quality disturbances under different noise background are conversed via grand-S transform, then eight characteristic vectors are put into na(?)ve Bayes classifier to get corresponding disturbance type. The performance of na(?)ve Bayes classifier and BP neural network classifier under different noise background is compared.For issues of power quality disturbances'de-noising, de-noising method based on Singular Value Decomposition (SVD) is put forward. The algorithm constructs attractor trajectory matrix and does SVD to the matrix. According to singular entropy and Percent of contribution to total energy (PCTE), the de-noising rank is obtained and the signal is reconstructed. The thesis compares reconstruct wave form of different reconstruct rank and the error of original signal and reconstruct signal is contrasted.According to voltage flicker measurement, voltage flicker detection method based on Mathe Matical (MM) filtering and Teager Energy Operator (TEO) is proposed. The multiple MM filter filters out pulse noise and white noise contained in fliker signal, then the filtered signal is tracked accurately and quikly via TEO. And modulation wave's characters can be got via Pisarenco. The algorithm is tested under different voltage flickers.Aiming at intantaneous protection algorithm of apparatus, intantaneous protection algorithm of apparatus based on grand MM filtering and fast deviation is proposed in this thesis. Grand MM filter removes aperiodic component and high frequency component contained in short circuit current signal, then applying fast deviation the amplitude of current can be obtained and short circuit faults can be removed quickly. The algorithm is tested under different short circuit phases.