Adaptive CWT‐based overcurrent protection for smart distribution grids considering CT saturation and high‐impedance fault. Issue 6 (31st January 2018)

• Record Type: Journal Article
• Authors: AsghariGovar, Saeed; Heidari, Saeid; Seyedi, Heresh; Ghasemzadeh, Saeid; Pourghasem, Pouya
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 6(2018)
• Page Start: 1366
• Page End: 1373
• Publication Date: 2018-01-31
• Subjects: overcurrent protection -- smart power grids -- power distribution protection -- power distribution faults -- power distribution reliability -- current transformers -- interpolation -- learning (artificial intelligence) -- wavelet transforms -- power engineering computing; adaptive CWT‐based overcurrent protection -- smart distribution grids -- CT saturation -- high‐impedance fault -- adaptive continuous wavelet transform -- current transformer saturation -- HIF occurrence -- three‐phase current waveforms -- frequency coefficient -- relay memory -- learning data -- real‐fault current -- nonlinear interpolation -- extreme learning machine approach -- time dial setting -- adaptive protection method; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2017.0887
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : In this study, an adaptive continuous wavelet transform (CWT)‐based overcurrent protection for smart grids is proposed to enhance the overcurrent protection performance encountering high‐impedance fault (HIF) and current transformer (CT) saturation, which are extremely complex phenomena and their impacts often cause mis‐coordination or mal‐operation. The proposed algorithm samples three phase current waveforms and imports them to CWT to extract high frequency coefficients. Afterwards, the sum of absolute values of the coefficients, S coef, is calculated for each sample during the last cycle. Meanwhile, several simulations related to HIFs with different impedances and CT saturations with different severities are executed and the fault currents and the sum of absolute values of the coefficients are achieved and saved in the relay memory as ( X, Y ) coordinates of points ( IL‐ fault, SL‐ coef ), named 'learning data'. Thereafter, each S coef is imported to the X − Y plane and, consequently, the occurrence of HIF or CT saturation is detected and the real‐fault current is estimated by both non‐linear interpolation and extreme learning machine approaches. Subsequently, new time dial setting and I pickup of the relays are computed and reloaded. Security, dependability, and sensitivity of the proposed adaptive protection method are confirmed by numerous simulation studies.