Journal Article

Fault detection in distribution networks in presence of distributed generations using a data mining–driven wavelet transform

Amraee, Turaj, Mohammadnian, Youness, Soroudi, Alireza

2019

Overview

Here, a data mining–driven scheme based on discrete wavelet transform (DWT) is proposed for high impedance fault (HIF) detection in active distribution networks. Correlation between the phase current signal and the related details of the current wavelet transform is presented as a new index for HIF detection. The proposed HIF detection method is implemented in two subsequent stages. In the first stage, the most important features for HIF detection are extracted using support vector machine (SVM) and decision tree (DT). The parameters of SVM are optimised using the genetic algorithm (GA) over the input scenarios. In second stage, SVM is utilised to classify the input data. The efficiency of the utilised SVM-based classifier is compared with a probabilistic neural network (PNN). A comprehensive list of scenarios including load switching, inrush current, solid short-circuit faults, HIF faults in the presence of harmonic loads is generated. The performance of the proposed algorithm is investigated for two active distribution networks including IEEE 13-Bus and IEEE 34-Bus systems.

• Publisher: The Institution of Engineering and Technology,John Wiley & Sons, Inc,Wiley
• Subject: active distribution networks / Algorithms / Approximation / B0230 Integral transforms / B0250 Combinatorial mathematics / B0260 Optimisation techniques / B8120K Distributed power generation / C1130 Integral transforms / C1140Z Other topics in statistics / C1160 Combinatorial mathematics / C1180 Optimisation techniques / C5290 Neural computing techniques / C6170K Knowledge engineering techniques / C7410B Power engineering computing / Classification / current wavelet / Data mining / data mining–driven scheme / decision tree / Decision trees / Discrete Wavelet Transform / discrete wavelet transforms / Distributed generation / distributed generations / distributed power generation / Fault detection / fault diagnosis / Feature selection / Genetic algorithms / HIF detection method / HIF faults / High impedance / high impedance fault detection / IEEE 13-Bus systems / IEEE 34-Bus systems / input data / Inrush current / Methods / neural nets / Neural networks / Phase current / phase current signal / power distribution faults / power engineering computing / probabilistic neural network / probability / Research Article / solid short-circuit faults / support vector machine / Support vector machines / utilised SVM-based classifier / Wavelet transforms