Power quality event characterization using support vector machine and optimization using advanced immune algorithm

A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances

“…A PQ disturbances classification system based on wavelet packet energy and multiclass SVM was proposed in [55] to discriminate seven types of PQ disturbances. In [146] authors proposed TT-transform (TTT) with a modified Gaussian window and SVM clustering to the problem of power signal classification. In [17] authors proposed WT based feature extraction, k-means based Apriori feature selection algorithm and Least Square SVM (LS-SVM) classifier algorithm for classification of the PQ events.…”

A Review of Classification Problems and Algorithms in Renewable Energy Applications

“…The problem is tackled as a multi-class classification problem with seven classes (corresponding to the seven different power quality disturbances to be detected) that obtains the predictive variables from the wavelet transform. In [121], an SVM classifier with different kernels is proposed for PQ detection. This work uses the time-time transform to obtain the predictive variables that represent the power signals.…”

Sistema de deteccion de eventos de calidad de energía basado en Maquinas de Vectores de Soporte

“…Por este motivo los investigadores se han volcado a métodos de clasificación más robustos como Hidden Markov Model [13], Gabor Wigner [5], Lógica Difusa [14] [15] o Máquinas de Soporte Vectorial (SVM, por sus siglas en inglés) [16].…”