H.M. Nabil^*, A.S. Emarah and M. EL-Shimy

Department of Electrical Power and Machine, Ain Shams University, Cairo, Egypt

Submitted on 24 January 2025; Accepted on 25 March 2025; Published on 17 April 2025

To cite this article: H.M. Nabil, A.S. Emarah and M. EL-Shimy, “Survey of Salient Voltage Sag Detection Methods in Power Systems,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 1, pp. 1-8, 2025.

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Abstract

Voltage sags are a frequent power quality issue that causes the root mean square (RMS) voltage to decrease from 10 milliseconds to 1 second. Even a slight drop can lead to serious problems, including equipment malfunctions, process interruptions, and financial losses. Therefore, timely and accurate detection of voltage sags is crucial to ensure system reliability and minimize potential damage. In this paper, we will review various voltage sag detection methods, including peak voltage detection, conventional d-q transform, discrete Fourier transform (DFT), wavelet transform (WT), Monte Carlo simulation, digital prolate spheroidal window (DPSW), and virtual positive sequence sag detection (VPS²D). Each method's implementation complexity, detection time, accuracy, and strength will be evaluated, even when harmonics and noise are present.

Keywords: voltage sag; detection methods; power quality

Abbreviations: RMS: root mean square; DFT: discrete Fourier transform; WT: wavelet transform; DPSW: digital prolate spheroidal window; VPS²D: virtual positive sequence sag detection; PLL: phase-locked loop; DPSS: discrete prolate spheroidal sequences; ST: Stockwell transform; CWT: continuous wavelet transform; DWT: discrete wavelet transform; VSC: voltage source converter; DSOGI-FLL: dual second-order generalized integrator frequency-locked loop; FLL: frequency-locked loop; HAS: High Accuracy Service; PRS: Public Regulated Services;