Hilbert Transform Based Simple Detection and Indice Analyze of Voltage Sags Using Synthetic Data

Abstract

Electrical grid has lots of changes in its morphology and managing style since first installed nearly two hundred years ago. Today, smart grid structure plays a crucial role when creating a sustainable and reliable operation. In smart grid context, power quality issues are monitored and required measures are obtained from smart meters. Power quality term include voltage quality. When it is about voltage quality, sags take the lead among other disturbances. System operators have to track voltage sags to provide a better service quality. In this study, a fast and simple algorithm called Hilbert Transform is used to detect voltage sags in synthetic dataset. Then, a voltage sag table is built considering related IEEE and IEC standards to identify site indices SARFI-X and SIARFI-X. Purpose of the study is being a first step to voltage sag detection and defining indices with real data. Obtained results denote and feed this aim.