Hampannavar, S.Teja, C.B.Swapna, M.Kumar, U.R.Y.2026-02-0620202020 IEEE International Conference on Power Electronics, Smart Grid and Renewable Energy, PESGRE 2020, 2020, Vol., , p. -https://doi.org/10.1109/PESGRE45664.2020.9070382https://idr.nitk.ac.in/handle/123456789/30850According 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.Blackman windowFIR filter designFrequency errorHamming windowHarmonics.Phasor measurement unitTotal vector error