Homogeneity-PMU-Based Method for Detection and Classification of Power Quality Disturbances

Jose Razo-Hernandez,Jose Rangel-Magdaleno,Juan Amezquita-Sanchez,Martin Valtierra-Rodriguez,Jose Gomez-Aguilar,David Granados-Lieberman

doi:10.3390/electronics7120433

Abstract

Over the past few years, power quality (PQ) monitoring has become of paramount importance for utilities and users since poor PQ generates negative consequences. In monitoring, fast detection and accurate classification of PQ disturbances (PQDs) are desirable features. In this work, a new method to detect and classify PQDs is proposed. The proposal takes advantage of the low computational resources of both a phasor measurement unit (PMU)-based signal processing scheme and the homogeneity approach. To classify the PQDs, if–then–else rules are used. To validate and test the proposal, synthetic and real signals of sags, swells, interruptions, notching, spikes, harmonics, and oscillatory transients are considered. For the generation of real signals, a PQD generator based on a power inverter is used. In the proposed method, the PMU information is directly used to classify sags, swells, and interruptions, whereas the homogeneity index is used to distinguish among the remaining PQDs. Results show that the proposal is an effective and suitable tool for PQ monitoring.

Highlights

The topic of power quality (PQ) is of paramount importance for utilities and users [1,2,3], since poorPQ negatively affects both electric network infrastructure and equipment connected to the power line.In general, poor PQ is associated with the presence of different electromagnetic phenomena, commonly called PQ disturbances (PQDs), in the voltage or current signals [4,5]
It consists of a personal computer (PC) with
A new method to detect and classify PQDs is presented. It is based on the phasor estimation model for P-class phasor measurement unit (PMU) and the homogeneity approach

Summary

Introduction

The topic of power quality (PQ) is of paramount importance for utilities and users [1,2,3], since poorPQ negatively affects both electric network infrastructure and equipment connected to the power line.In general, poor PQ is associated with the presence of different electromagnetic phenomena, commonly called PQ disturbances (PQDs), in the voltage or current signals [4,5]. There are several problems associated with modern power systems, such as a massive proliferation of non-linear loads that generate harmonic content and a distributed generation that produces intermittent and variable power [8,9,10,11]. These require the development of both new technologies to reduce their negative impact, such as compensators, active filters, and energy storage systems, among others [9,11,12], and PQ monitoring systems that provide information about the voltage and current waveforms for further processing and analysis

Methods

Results

Discussion

Conclusion