Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3701
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dc.contributor.authorSingh, Bikash Swarup Bidyasagar-
dc.contributor.authorRai, Shekha-
dc.date.accessioned2022-07-27T10:26:41Z-
dc.date.available2022-07-27T10:26:41Z-
dc.date.issued2022-05-
dc.identifier.citation3rd International Conference for Emerging Technology (INCET) Belgaum, India. May 27-29, 2022en_US
dc.identifier.urihttp://hdl.handle.net/2080/3701-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractThis paper proposes a Machine learning (ML) based Eigen Realization algorithm (ERA) for real-time estimation of poorly damped modes in power system. The proposed technique is designed in such a way that it mitigates the effects of data loss and presence of outliers from the Phasor Measurement Unit (PMU) which occurs because of communication delay, hardware faults etc. There is an enhancement in ERA algorithm where a fast-computing weighted moving average (WMA) and inter-Quartile range (IQR), combinedly called WMA-IQR filter has been introduced to take care of the incomplete measurements and outliers respectively present in the system. Finally, the ERAalgorithm is applied using a robust data set to give a precise value of the modes. The robust performance of the proposed scheme over the ERA and modified ERA estimator has been illustrated on some simulations carried out on synthetic signals and real signal collected from WECC.en_US
dc.subjectMLen_US
dc.subjectPMUen_US
dc.subjectERAen_US
dc.subjectWMA-IQR filter, Phasor, WECCen_US
dc.titleAn ML-based ERA Algorithm for Estimation of Modes Utilizing PMU Measurementsen_US
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