Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System

This paper presents a variational mode decomposition (VMD) and decision tree based detection and classification method of single and mixed power quality (PQ) disturbances in grid-connected distributed generation system. Applicability of VMD technique is investigated for discrimination of stationary PQ disturbances (such as harmonics, interharmonics, and flicker), non-stationary events (e.g., transients) and noise. Studies indicate usefulness of VMD for accurate estimation of phasor quantities such as amplitude, phase angle, and frequency and other describing features. Features namely, mode central frequencies, relative mode energy ratios, zero crossings, and instantaneous amplitude (IA) are extracted for classification of single and mixed PQ disturbances using a decision tree algorithm. A set of synthetic test signals, disturbance signals obtained from real events as well as signals generated from real time digital simulator platform arc used to test effectiveness of proposed method, under various system operating scenarios and noise levels. Proposed method is found to be capable of accurate detection, estimation, localization, and classification of all kinds of PQ disturbances in both noisy and noise-free cases.