A multivariable transmission line protection scheme using signal processing techniques. Issue 22 (28th June 2021)

• Record Type: Journal Article
• Authors: Gupta, Abhishek; Pachar, Ramesh Kumar; Khan, Baseem; Mahela, Om Prakash; Padmanaban, Sanjeevikumar
• Is Part Of: IET generation, transmission & distribution. Volume 15:Issue 22(2021)
• Page Start: 3115
• Page End: 3137
• Publication Date: 2021-06-28
• Subjects: Integral transforms -- Signal processing and detection -- Power transmission lines and cables -- Power system protection -- Integral transforms -- Digital signal processing -- Power engineering computing; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/gtd2.12244
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract: This paper introduced an advanced algorithm making hybrid use of Stockwell transform (ST), Hilbert transform (HT) and Alienation coefficient (ACF) for identification, classification and to locate faulty events on transmission line. Signals of Current are processed by application of ST, HT and ACF for computing S‐index, H‐index and A‐index, respectively. These indices are multiplied element by element to compute proposed fault index (FI). A threshold magnitude is decided after testing the algorithm during different fault scenarios and faulty events are recognized when FI exceeds this threshold magnitude. Faults are categorized by identifying the number of phases which are faulty in nature and a ground fault index (GFI). GFI is designed by processing the zero sequence current using ST and used to identify involvement of ground during fault event. A mathematical formulation is framed to estimate location of faults on transmission line. Fault location has been estimated with a mean error less than 1%. Investigated faults include phase to ground (PGF), double phase (PPF), double phase to ground (PPGF) and three phase to ground (TPGF). Algorithm is found effective for faulty scenario such as fault impedance variations, fault incidence angle (FIA) variations, reverse power flow, effect of line loading, effect of noise, transient faults, off‐nominal frequency, and presence of harmonic components. Algorithm is also effective for discriminating switching transients from faulty conditions. Effective performance of the algorithm is established by comparing with fault detection and classification approach based on alienation coefficients, discrete Fourier transform (DFT) and time‐frequency approach. Study is performed on a two terminal transmission line in MATLAB/Simulink environment. Effectiveness of the algorithm is also established on a real time transmission grid of Rajasthan state of India.