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Instantaneous Faults Detection in Power System

Authors: Richard Binns; Salwa Juma Al-Mamari; Mehdi Salehifar;

Instantaneous Faults Detection in Power System

Abstract

Power quality covers a wide range of issues that affect utilities and consumers. Problems associated with power quality can be classified into different categories. Interruption, sag, swell, voltage and frequency variation. These are typical faults that could lead to a serious damage in a power network. This paper presents a proposed MATLAB model that could be an accurate, cheap and affordable solution for the instantaneous detection of interruption, sags, swells, harmonic content, frequency and voltage variations, of an input signal that can occur during the normal and up-normal operation of a power system. The system is designed to operate on a 230 V, 50 Hz grid signal for a period of time defined by the network operators. The proposed model consists of fault detectors and noise filtering methods that were designed using MATLAB algorithms and simple mathematical equations. Several tests have been conducted on the suggested model; the fault detectors were able to detect about 97.33% of overall tested faults on the model (sag, swell, interruption, frequency and voltage variations).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
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