Design and Implementation of Arcing Detection on Low Voltage with Evaluation of Discrete Wavelet Transform

Abdul Rahman Wachid*, Dimas Anton Asfani, I. Made Yulistya Negara, Arief Budi Ksatria

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this study, parallel arcing detection is designed and implemented. Arcing is one of the disturbances in electrical power systems. The fault current generated by arcing typically happens very quickly with a short period. This study focuses on designing a hardware device for parallel arcing fault detection. The algorithm in this research is using wavelet transform as a signal processing technique by considering the selection of the mother wavelet and decomposition for optimizing parameters of the DWT method. The system of this DWT is to transform the maximum current values read by the hardware into an output signal called the detail coefficient of the current maximum. Based on the DWT output data in normal and switching conditions, the maximum detail coefficient value obtained is 150, with 3 points having this value. Therefore, to detect parallel arcing, two thresholds are used: the detail coefficient current maximum value should be ≥150, and the number of fault points should be ≥3 points. In this study, DWT parameters were evaluated by using 3 different variations of mother wavelet and 2 variations of decomposition level to determine the best arcing detection results. From the results obtained, it shows that the use of mother wavelet parameter Coiflet 4 and decomposition level 5 is the best DWT performance in detecting parallel arcing faults with a maximum current coefficient detail output value of 3108 and number of fault points at 5 points.

Original languageEnglish
Title of host publication2024 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationCollaborative Innovation: A Bridging from Academia to Industry towards Sustainable Strategic Partnership, ISITIA 2024 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages536-541
Number of pages6
Edition2024
ISBN (Electronic)9798350378573
DOIs
Publication statusPublished - 2024
Event25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024 - Hybrid, Mataram, Indonesia
Duration: 10 Jul 202412 Jul 2024

Conference

Conference25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024
Country/TerritoryIndonesia
CityHybrid, Mataram
Period10/07/2412/07/24

Keywords

  • Arcing Detection
  • Decomposition
  • Discrete Wavelet Transform
  • Low Voltage
  • Mother wavelet

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