Automated Power Quality Monitoring System for On-line Detection and Classification of Disturbances

Abstract

This paper presents a system for detection and classification of power quality (PQ) voltage disturbances. The proposed system applies the following methods to detect and classify the PQ disturbances: digital filtering and mathematical morphology are used to detect and classify transients and waveform distortions, while in case of short and long duration disturbances (such as sags, swells and interruptions) the analysis of the RMS value of the voltage is employed. The decision and classification process is based on disturbances knowledge base of an expert system. The proposed approach identifies the type of the disturbance and its parameters such as time localization, duration and magnitude. The proposed system is suitable for on-line monitoring of the power system and for implementation in a digital signal processor (DSP).