In today's expanding energy landscape, the integration of distributed energy resources (DERs) into distribution grids introduces reliability challenges due to the uncertain and intricate behaviors of these resources. As DER penetration in distribution grids increases, traditional outage detection methods reliant on signals from measuring instruments exhibit inadequate performance, as renewable generators and storage can continue supplying power post-line outages. Numerous electrical parameters undergo notable changes after outages. In this research, we utilized voltage, power, and power angle measurements captured by SMs to detect outage occurrences. We propose a data-driven outage monitoring methodology based on Intrinsic Time Decomposition (ITD). Here, the instantaneous phase voltage measured by SMs from various buses are decomposed by ITD into various modes to estimate energy, and is used as detection index. The technique employs an adaptive threshold selection method to identify outage. To validate the algorithm's efficacy, we consider the Indian Eastern Regional Grid (IERG) network, which is simulated in EMTDC/PSCAD.
Outage Area Identification in Smart Grid: An Adaptive Approach
31.07.2024
547855 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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