High impedance faults detection in power distribution networks using rogowski coils, kalman filtering, least-squares and non-recursive DFT computation engines
Ziad M. Ali, Mostafa H. Mostafa, Shady H. E. Abdel Aleem, Ehab M. Esmail
TL;DR
This paper introduces a new method for detecting high-resistance faults in power networks using a non-recursive DFT approach, which outperforms existing techniques.
Contribution
The novel non-recursive DFT computational engine for high-impedance fault detection is introduced and validated.
Findings
The non-recursive DFT method showed a fixed amplitude error and rotated output angle during transient errors.
The proposed technique outperformed current reconstruction, Kalman filtering, and least-squares methods in fault detection.
Simulations using MATLAB confirmed the effectiveness of the new method under various arc models and test conditions.
Abstract
This paper presents a novel computational engine based on non-recursive discrete Fourier transform (DFT) technology to detect high-resistance faults (HRFs) in power distribution networks. The non-recursive DFT approach utilizes the interconnection between a sliding window for current signals and a foundation function window during transient error. This non-recursive DFT technology is characterized by a fixed error in amplitude calculation and a rotated output angle. The proposed technique is compared against several established methods for high-resistance fault detection in distribution systems, including current reconstruction (CR) using Rogowski coils, Kalman filtering, and least-squares computational engines. The performance of each technique is evaluated by assessing the estimated percentage error in the calculation of fundamental and harmonic amplitudes. To study the proposed…
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Taxonomy
TopicsPower Systems Fault Detection · Electrical Fault Detection and Protection · High voltage insulation and dielectric phenomena