Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/14996
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dc.contributor.authorHampannavar S.
dc.contributor.authorTeja C.B.
dc.contributor.authorSwapna M.
dc.contributor.authorKumar U.R.Y.
dc.date.accessioned2021-05-05T10:16:10Z-
dc.date.available2021-05-05T10:16:10Z-
dc.date.issued2020
dc.identifier.citation2020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy, PESGRE 2020 , Vol. , , p. -en_US
dc.identifier.urihttps://doi.org/10.1109/PESGRE45664.2020.9070382
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14996-
dc.description.abstractAccording to the standard C37.118.1, Phasor Measurement Units (PMU) can be broadly classified into two classes: Measurement (M) and Performance (P), where P-Class is used when faster output latency is required and M-Class is used for measurement applications which requires high precision. The standard presents Hamming window as a reference algorithm for M-Class PMU whereas, in this paper we use Blackman window algorithm. The performance of M-Class PMU is analyzed with both the algorithms by taking two case studies in which input given to the PMU is contaminated with different levels of harmonics, inter-harmonics and frequency ramps in each case and it is found that, the errors in frequency and rate of change of frequency (ROCOF) measured by PMU are reduced by a factor of >100 with the Blackman window algorithm when compared to a Hamming window algorithm (which is specified in the standard). © 2020 IEEE.en_US
dc.titlePerformance Improvement of M-Class Phasor Measurement Unit (PMU) using Hamming and Blackman Windowsen_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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