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Fault Detection in an ADN using Local Mean Decomposition

dc.contributor.authorPandey A.K.; Kishor K.; Mohanty S.R.; Samuel P.
dc.date.accessioned2025-05-23T11:24:03Z
dc.description.abstractProliferation of distributed generation (DG) in distribution systems has given rise to new protection challenges. This paper aims to address such challenges by proposing a new fault detection scheme based on Local Mean Decomposition (LMD). The relay currents are locally measured and are subjected to LMD to obtain product functions (PFs). The most significant PF is then subjected to moving window singular value decomposition (SVD) to obtain the index for fault detection. The detection scheme is tested on a 33 bus radial distribution network with DG simulated in MATLAB/Simulink. The detection scheme gives encouraging results regarding fault detection and is also capable of discriminating between fault and non-fault transients. © 2022 IEEE.
dc.identifier.doihttps://doi.org/10.1109/STPES54845.2022.10006504
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/9677
dc.relation.ispartofseries2022 1st International Conference on Sustainable Technology for Power and Energy Systems, STPES 2022
dc.titleFault Detection in an ADN using Local Mean Decomposition

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