Classification of Power Quality Disturbances in Emerging Power System with Distributed Generation Using Space Phasor Model and Normalized Cross Correlation

Abstract

This paper introduces a new method for detecting and classifying power quality disturbances (PQDs) in emerging power system with Distributed Generation (DG). The Space Phasor Model (SPM) and Normalized Cross-Correlation (NCC) based image pattern (template) matching algorithm is proposed to detect and classify the PQDs. An emerging power system with DG system is simulated in MATLAB Simulink environment. In this paper, seven PQDs namely voltage sag, voltage swell, voltage interruption, oscillatory transients, voltage flicker, voltage notch, and voltage harmonics with notch which are caused by the DG operating conditions, and other causes are considered under study. The space phasor models represented in the complex plane are obtained for each case of PQDs using the three-phase voltage signals. The NCC-based image pattern matching technique is used to convert these space phasor models into template and matching images for the detection and classification of PQDs. The graphical results show that the proposed algorithm accurately detects and classifies the PQD provided in the template image by finding its exact match and position in the matching image.