Self-Healing of Active Distribution Networks by Accurate Fault Detection, Classification, and Location

The power system self-healing concept needs accurate and reliable fault detection, classification, and location (FDCL). This research proposes a novel and robust FDCL approach for distribution networks (DNs) in proportion to self-healing requirements. The proposed algorithm utilized a discrete wavel...

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Bibliographic Details
Published in:Journal of electrical and computer engineering 2022-03, Vol.2022, p.1-14
Main Authors: El-Tawab, Sally, Mohamed, Hassan S., Refky, Amr, Abdel-Aziz, A. M.
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Classification
Decomposition
Discrete Wavelet Transform
Distributed generation
Fault detection
Fault diagnosis
Fault location
Fourier transforms
Measurement techniques
Methods
Signal processing
Substations
Support vector machines
Training
Wavelet transforms
Zero sequence current
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Summary:The power system self-healing concept needs accurate and reliable fault detection, classification, and location (FDCL). This research proposes a novel and robust FDCL approach for distribution networks (DNs) in proportion to self-healing requirements. The proposed algorithm utilized a discrete wavelet transform (DWT) to decompose the measured current and zero sequence current component of only one terminal (substation) to detect and classify all fault types with the identification of the faulted phase (s). The fault location is achieved by integrating DWT and support vector machine (SVM). The data for training were extracted using DWT and collected, and then SVM was trained to locate the faulted section. The simplicity of the applied approach, ignoring DG’s data that is merged into the system, reduced training data and time, ability to diagnose all fault types, and high accuracy are the most significant contributions. The proposed techniques are tested on IEEE 33 bus DN with two distributed generation (DG) units, which are simulated in MATLAB. The simulation results demonstrate that the proposed methods give more accurate and reliable results for diagnosing the faults (FDCL) of various fault sorts, DN size, and resistance levels.
ISSN:2090-0147
2090-0155
DOI:10.1155/2022/4593108