Di̇nami̇k Geri̇li̇m İyi̇leşti̇ri̇ci̇lerde Geri̇li̇m Problemleri̇ni̇n Tespi̇ti̇ İçi̇n Yeni̇ Yöntem Geli̇şti̇ri̇lmesi̇

İnci, Mustafa; Bayındır, Kamil Çağatay; Tümay, Mehmet

doi:10.17341/gazimmfd.278455

Cited by 1 publication

(1 citation statement)

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“…Voltage sag, which can be identified as the decrease in voltage amplitude between 0.1 and 0.9 pu in a time from 10 milliseconds to a minute, is one of the important power quality problems encountered in transmission and distribution systems [12]. The main reason for the voltage sag is phase-to-ground and phase-to-phase faults, and it causes shutdown, incorrect operation or malfunction of power electronics-based systems, and undesired operation due to low voltage in relay and contactor coils [13,14]. Researchers have usually focused on the classification, detection, and evaluation of voltage sag.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Voltage Sag Relative Location with Data-Driven Algorithms in Distribution Grid

et al. 2022

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Power quality (PQ) problems, including voltage sag, flicker, and harmonics, are the main concerns for the grid operator. Among these disturbances, voltage sag, which affects the sensitive loads in the interconnected system, is a crucial problem in the transmission and distribution systems. The determination of the voltage sag relative location as a downstream (DS) and upstream (US) is an important issue that should be considered when mitigating the sag problem. Therefore, this paper proposes a novel approach to determine the voltage sag relative location based on voltage sag event records of the power quality monitoring system (PQMS) in the real distribution system. By this method, the relative location of voltage sag is defined by Gaussian naive Bayes (Gaussian NB) and K-nearest neighbors (K-NN) algorithms. The proposed methods are compared with support vector machine (SVM) and artificial neural network (ANN). The results indicate that K-NN and Gaussian NB algorithms define the relative location of a voltage sag with 98.75% and 97.34% accuracy, respectively.

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Section: Introductionmentioning

confidence: 99%