The Detection of Power System Faults Using Different Time-Frequency Domain Methods

Zafer Doğan

Makale detayları

The Detection of Power System Faults Using Different Time-Frequency Domain Methods

Yazarlar:

Zafer Doğan

Yayıncı:

Tokat Gaziosmanpasa University

Ana Başlıklar:

Elektrik Tesisleri

Dergi:

Gaziosmanpaşa Bilimsel Araştırma Dergisi Vol.13 Issue 1, pp.126-134

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001318518

pISSN:

2146-8168

Anahtar kelimeler:

Özet:

 This papers approach evaluates the effect of faults on stability parameters, acknowledging the crucial role of power system stability. This integration aims to provide a thorough grasp of the relationship between defect detection and system stability. Phase-to-phase and phase-to-ground fault detection in power systems is the main emphasis of this research. Through the use of Wavelet Transform WT, Hilbert-Huang Transform HHT, and Short-Time Fourier Transform STFT, our study offers a thorough analysis by capturing both time and frequency features. We detail the techniques WT, HHT, and STFT application principles, highlighting the significance of real-time sampling of voltage and current behaviors during faults. This improves the depth of our fault detection analysis. We use a pertinent dataset to investigate phase-to-phase and phase-to-ground faults, adopting preprocessing for strong data quality. Including faults makes it possible to sample and observe voltage and current behaviors in real-time, giving information about the power systems dynamic reaction. The methods performance in fault identification is illustrated using visual aids, and the results are given and debated. The effects of dynamic variations in voltage and current behaviors on the stability of the power system are emphasized during failure situations. Our findings are more significant when seen in the larger context of creating a stable and resilient power grid, thanks to the inclusion of power system stability analysis.

 This papers approach evaluates the effect of faults on stability parameters, acknowledging the crucial role of power system stability. This integration aims to provide a thorough grasp of the relationship between defect detection and system stability. Phase-to-phase and phase-to-ground fault detection in power systems is the main emphasis of this research. Through the use of Wavelet Transform WT, Hilbert-Huang Transform HHT, and Short-Time Fourier Transform STFT, our study offers a thorough analysis by capturing both time and frequency features. We detail the techniques WT, HHT, and STFT application principles, highlighting the significance of real-time sampling of voltage and current behaviors during faults. This improves the depth of our fault detection analysis. We use a pertinent dataset to investigate phase-to-phase and phase-to-ground faults, adopting preprocessing for strong data quality. Including faults makes it possible to sample and observe voltage and current behaviors in real-time, giving information about the power systems dynamic reaction. The methods performance in fault identification is illustrated using visual aids, and the results are given and debated. The effects of dynamic variations in voltage and current behaviors on the stability of the power system are emphasized during failure situations. Our findings are more significant when seen in the larger context of creating a stable and resilient power grid, thanks to the inclusion of power system stability analysis.

 This papers approach evaluates the effect of faults on stability parameters, acknowledging the crucial role of power system stability. This integration aims to provide a thorough grasp of the relationship between defect detection and system stability. Phase-to-phase and phase-to-ground fault detection in power systems is the main emphasis of this research. Through the use of Wavelet Transform WT, Hilbert-Huang Transform HHT, and Short-Time Fourier Transform STFT, our study offers a thorough analysis by capturing both time and frequency features. We detail the techniques WT, HHT, and STFT application principles, highlighting the significance of real-time sampling of voltage and current behaviors during faults. This improves the depth of our fault detection analysis. We use a pertinent dataset to investigate phase-to-phase and phase-to-ground faults, adopting preprocessing for strong data quality. Including faults makes it possible to sample and observe voltage and current behaviors in real-time, giving information about the power systems dynamic reaction. The methods performance in fault identification is illustrated using visual aids, and the results are given and debated. The effects of dynamic variations in voltage and current behaviors on the stability of the power system are emphasized during failure situations. Our findings are more significant when seen in the larger context of creating a stable and resilient power grid, thanks to the inclusion of power system stability analysis.

 Bu makalenin yaklaşımı, güç sistemi kararlılığının kritik rolünü kabul ederek, arızaların kararlılık parametreleri üzerindeki etkisini değerlendirmektedir. Bu entegrasyon, kusur tespiti ile sistem kararlılığı arasındaki ilişkinin kapsamlı bir şekilde anlaşılmasını sağlamayı amaçlamaktadır. Güç sistemlerinde faz-faz ve faz-toprak arıza tespiti bu araştırmanın ana vurgusunu oluşturmaktadır. Dalgacık Dönüşümü WT, Hilbert-Huang Dönüşümü HHT ve Kısa Zamanlı Fourier Dönüşümü STFT kullanımı sayesinde çalışmamız hem zaman hem de frekans özelliklerini yakalayarak kapsamlı bir analiz sunmaktadır. Tekniğin WT, HHT ve STFT uygulama prensiplerini detaylandırarak, arızalar sırasında gerilim ve akım davranışlarının gerçek zamanlı örneklemesinin önemini vurguluyoruz. Bu, arıza tespit analizimizin derinliğini artırır. Güçlü veri kalitesi için ön işlemeyi benimseyerek fazdan faza ve fazdan toprağa arızaları araştırmak için uygun bir veri seti kullanıyoruz. Arızaların dahil edilmesi, gerilim ve akım davranışlarının gerçek zamanlı olarak örneklenmesine ve gözlemlenmesine olanak tanıyarak, güç sisteminin dinamik tepkisi hakkında bilgi verir. Yöntemin arıza tespitindeki performansı görsel araçlarla gösterilmiş, sonuçlar verilmiş ve tartışılmıştır. Arıza durumlarında gerilim ve akım davranışlarındaki dinamik değişimlerin güç sisteminin kararlılığı üzerindeki etkileri vurgulanmaktadır. Bulgularımız, güç sistemi stabilite analizinin dahil edilmesi sayesinde istikrarlı ve dayanıklı bir enerji şebekesi yaratmaya yönelik daha geniş bir bağlamda görüldüğünde daha anlamlıdır.

Makale detayları

The Detection of Power System Faults Using Different Time-Frequency Domain Methods

Yazarlar:

Zafer Doğan

Yayıncı:

Tokat Gaziosmanpasa University

Ana Başlıklar:

Elektrik Tesisleri

Dergi:

Gaziosmanpaşa Bilimsel Araştırma Dergisi Vol.13 Issue 1, pp.126-134

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001318518

pISSN:

2146-8168

power system

fault detection

time-frequency domain

distribution faults

power system fault diagnosis

wavelet transform

Hilbert Huang transform

STFTgüç sistemi

arıza tespiti

zaman-frekans boyutu

dağıtım arızaları

güç sistemi arıza teşhisi

dalgacık dönüşümü

Hilbert Huang dönüşümü

STFT

Sayı

Makale detayları

Yazarlar: Zafer Doğan

Yayıncı: Tokat Gaziosmanpasa University

Ana Başlıklar: Elektrik Tesisleri

Dergi: Gaziosmanpaşa Bilimsel Araştırma Dergisi Vol.13 Issue 1, pp.126-134

Belge Tipi: Makale

Yayın Tarihi: 12/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001318518

pISSN: 2146-8168

Sayı

Yazarlar:

Zafer Doğan

Yayıncı:

Tokat Gaziosmanpasa University

Ana Başlıklar:

Elektrik Tesisleri

Dergi:

Gaziosmanpaşa Bilimsel Araştırma Dergisi Vol.13 Issue 1, pp.126-134

Belge Tipi:

Makale

Yayın Tarihi:

12/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001318518

pISSN:

2146-8168