Survey of Salient Voltage Sag Detection Methods in Power Systems

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.