1996
DOI: 10.1109/61.517531
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Identification and tracking of harmonic sources in a power system using a Kalman filter

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Cited by 141 publications
(12 citation statements)
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“…The state vectors at the th k and   th 1 k  sampling instant, state transition matrix   D and measurement matrix   H of the LKF are given by (15), (16), (17) and (18), respectively, where T denotes the transpose operation. The transition matrix given in (17) is obtained from the expressions (15) and (16).…”
Section: Rejection Of DC Offset and Harmonicsmentioning
confidence: 99%
See 1 more Smart Citation
“…The state vectors at the th k and   th 1 k  sampling instant, state transition matrix   D and measurement matrix   H of the LKF are given by (15), (16), (17) and (18), respectively, where T denotes the transpose operation. The transition matrix given in (17) is obtained from the expressions (15) and (16).…”
Section: Rejection Of DC Offset and Harmonicsmentioning
confidence: 99%
“…The orthogonal waveforms of grid fundamental frequency component are extracted using the SOGI. On the other hand, the DC offset and harmonics are rejected using the LKF [15][16][17] . The results of the proposed technique are compared with the MSOGI technique.…”
Section: Introductionmentioning
confidence: 99%
“…The time-frequency techniques merge the advantages of the time-domain and frequency-domain techniques, but they are mathematically complicated as shown by Barros and Diego (2008). State-estimation or state-space techniques have been developed to attain the merits of both time-domain and frequency-domain techniques as explained by Dash et al (1997), Haili and Girgis (1996), Soliman and El-hawary (2000), Karimi et al (2003), and Banas (1975). Nevertheless, the state-estimation techniques are superior to the traditional ones, they have some shortcomings.…”
Section: Introductionmentioning
confidence: 96%
“…Nevertheless, the state-estimation techniques are superior to the traditional ones, they have some shortcomings. For instance, the Kalman filter has mathematical burden as shown by Haili and Girgis (1996). The least-absolute value shares the Kalman filter the same shortcoming as illustrated by Soliman and El-hawary (2000).…”
Section: Introductionmentioning
confidence: 96%
“…In [5], HSE is performed by using the least-square based state estimation to compute the frequency spectra at various buses that are suspected as harmonic sources. The authors in [6] have identified and tracked the harmonic sources present in the power system using the conventional Kalman filter technique. In [7], wavelet transform is described as more suitable for small frequency varying signals; however, this method suffers from a high computational burden.…”
Section: Introductionmentioning
confidence: 99%