Rapid Power Quality Detection Based on Generalized HS-Transform

Abstract

In this paper, the hyperbolic S-transform (HS-transform) has been generalized with the introduction of the whole time frequency regulation factor and making the HS window function proportional to the square root of the frequency. Meanwhile, combined with the idea of incomplete S-transform, a rapid power quality detection based on generalized HS-transform (GHST) is proposed. Firstly, the fast Fourier transform (FFT) was performed and dynamic measurement was utilized to describe the envelope of power spectrum so as to detect the valid frequency samples of FFT. Then the GHST was specifically performed for these samples and a complex matrix was generated. Finally, these feature vectors extracted from the complex matrix were used to detect the power quality disturbances. Simulation results demonstrate that the proposed method can accurately detect the power quality disturbances with high computation speed and low sensitivity to noise, and it is suitable for practical applications.

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

“…This is found as a best detection technique in a noisy environment [78]. The other S-transform reported in the literature includes, discrete orthogonal S-transform [79], hybrid S-transform [80], generalized hyperbolic ST [81], Modified ST with random forest tree [82], ST and DT [83], Multi-resolution S transform (MST) [84], discrete ST [85], ST-extreme learning machine (ELM) [86], rule-based ST [87] and experimental validation of non-stationary signal parameters under the spectrum leakage using nonergodic S-transform (NEST) [88]. Recognition and assessment of various factors associated with wind turbines [89] and hybrid Solar Photo-Voltaic (SPV), Fuel Cell (FC), and Wind Energy (WE) penetration have been presented in [90].…”