High impedance fault detection in radial distribution network using discrete wavelet transform technique

• Autorzy: Suliman Mohammed Yahya , Alkhayyat Mahmood Taha

Identyfikatory

DOI

10.24425/aee.2021.138267

• Języki publikacji: EN

Abstrakty

EN

Detecting high impedance faults (HIFs) is one of the challenging issues for electrical engineers. This type of fault occurs often when one of the overhead conductors is downed and makes contact with the ground, causing a high-voltage conductor to be within the reach of personnel. As the wavelet transform (WT) technique is a powerful tool for transient analysis of fault signals and gives information both on the time domain and frequency domain, this technique has been considered for an unconventional fault like high impedance fault. This paper presents a new technique that utilizes the features of energy contents in detail coefficients (D4 and D5) from the extracted current signal using a discrete wavelet transform in the multiresolution analysis (MRA). The adaptive neurofuzzy inference system (ANFIS) is utilized as a machine learning technique to discriminate HIF from other transient phenomena such as capacitor or load switching, the new protection designed scheme is fully analyzed using MATLAB feeding practical fault data. Simulation studies reveal that the proposed protection is able to detect HIFs in a distribution network with high reliability and can successfully differentiate high impedance faults from other transients.

Słowa kluczowe

EN

high impedance fault; HIF; multiresolution analysis; MRA; overcurrent relays; discrete wavelet transform; DWT

PL

uszkodzenie o wysokiej impedancji; analiza wielorozdzielcza; przekaźniki nadprądowe; dyskretna transformata falkowa

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2021
• Tom: Vol. 70, nr 4
• Strony: 873--886
• Opis fizyczny: Bibliogr. 30 poz., tab., wz.

Twórcy

autor

Suliman Mohammed Yahya

• Northern Technical University, Iraq

• https://orcid.org/0000-0002-1250-6362+

autor

Alkhayyat Mahmood Taha

• Northern Technical University Iraq

• https://orcid.org/0000-0001-6119-7845

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).