@article{article_1464239, title={The Detection of Power System Faults Using Different Time-Frequency Domain Methods}, journal={Gaziosmanpaşa Bilimsel Araştırma Dergisi}, volume={13}, pages={126–134}, year={2024}, author={Bin Shafique, Hamza and Doğan, Zafer}, keywords={power system, fault detection, time-frequency domain, distribution faults, power system fault diagnosis, wavelet transform, Hilbert Huang transform, STFT}, abstract={This paper’s 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 technique’s 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 system’s dynamic reaction. The method’s 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.}, number={1}, publisher={Tokat Gaziosmanpasa University}