Volume 11, Issue 3 (11-2021)
JEM 2021, 11(3): 54-65 |
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Moravej Z, Ghahremani M. Detection of High Impedance Faults in Distribution Networks Using Stationary Wavelet Transform. JEM 2021; 11 (3) :54-65
URL: http://energy.kashanu.ac.ir/article-1-1469-en.html
URL: http://energy.kashanu.ac.ir/article-1-1469-en.html
Faculty of Electrical and Computer Engineering, Semnan University
Abstract: (2012 Views)
Introduction: In this paper, a new method for detecting high impedance fault in distribution networks is presented. In the proposed method, the Stationary Wavelet Transform (SWT) is used to extract features. Disturbance detection algorithm in the network, using changes in the selected features in the data windows after the fault occurrence, compared with the data windows before the fault occurrence, detects the high impedance fault. It, also, uses the vote-based decision-making system based on the aggregation of the output of the PNN classification, and the use of three post-disturbance data windows has improved the reliability of the proposed method. The results of the proposed method for detecting high impedance fault on the 34-node IEEE in the EMTP-RV software indicate the accuracy, reliability, and security of the proposed method at a high level.
Materials and methods: In the proposed method, the Stationary Wavelet Transform (SWT) was used to extract features, and a vote-based decision-making system using PNN for classification was deployed.
Result: The results of the method for detecting high impedance fault on the 34-node IEEE in the EMTP-RV software indicate the accuracy, reliability, and security of the proposed method at a high level.
Discussion and Conclusion: In this paper, an accurate and safe method for high impedance fault detection has been proposed. The proposed method uses the features extracted from the voltage and current through the Stationary Wavelet Transform (SWT), and it correctly detects the differences between high impedance fault and other distribution system events. It also uses the vote-based decision-making system based on the aggregation of the output of the PNN for classification, and reliability has increased. The results of the proposed method indicate the optimal performance of this method for detecting a high impedance fault.
Materials and methods: In the proposed method, the Stationary Wavelet Transform (SWT) was used to extract features, and a vote-based decision-making system using PNN for classification was deployed.
Result: The results of the method for detecting high impedance fault on the 34-node IEEE in the EMTP-RV software indicate the accuracy, reliability, and security of the proposed method at a high level.
Discussion and Conclusion: In this paper, an accurate and safe method for high impedance fault detection has been proposed. The proposed method uses the features extracted from the voltage and current through the Stationary Wavelet Transform (SWT), and it correctly detects the differences between high impedance fault and other distribution system events. It also uses the vote-based decision-making system based on the aggregation of the output of the PNN for classification, and reliability has increased. The results of the proposed method indicate the optimal performance of this method for detecting a high impedance fault.
Keywords: High impedance fault, distribution networks, Stationary Wavelet Transform (SWT), Disturbance detection, Probabilistic Neural Network
Type of Study: Research |
Subject:
Electrical Engineering
Received: 2020/05/21 | Revised: 2022/01/2 | Accepted: 2020/11/14 | Published: 2021/11/1
Received: 2020/05/21 | Revised: 2022/01/2 | Accepted: 2020/11/14 | Published: 2021/11/1
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