global-journal-of-research-in-engineering-f-electrical-electronic Global Journal of Research in Engineering - F: Electrical & Electronic 0975-5861 2249-4596 Global Journals Publishing Group Incorporated 73949 Linear Kalman Filter Algorithm with Clarke Transformation for Power System Frequency Estimation. SolimanProf. A. R.A.AlammariAl-Kandari EGYPT, Misr University for Science and Technology 15 03 2012 12 1 7 16

This paper presents a new application for linear Kalman filter algorithm for power system frequency estimation. The filter uses the digitized samples of the three-phase voltages or current waveform signals. These three phases are transformed into two αβγ -phases, using the well-known αβγ -transformation matrix. Having obtained the signal of the two new phases, a complex phasor is constructed using the new two-phase voltages. Kalman filter is then applied to extract the frequency and phase angle of the fundamental component of the complex and actual recorded phasor. The proposed algorithm is tested on simulated data at different conditions for the three phase signals; noise free and balanced three phase signals, unbalanced three-phase system and harmonics contaminated three phase signals. It has been shown that the proposed filters with the proposed transformation are succeeded to estimate the signal frequency at off nominal, near nominal and at nominal frequency.

 Linear Kalman filter frequency estimation αβ-transformation. αβ-transformation. Full Text

This paper presents a new application for linear Kalman filter algorithm for power system frequency estimation. The filter uses the digitized samples of the three-phase voltages or current waveform signals. These three phases are transformed into two αβγ -phases, using the well-known αβγ -transformation matrix. Having obtained the signal of the two new phases, a complex phasor is constructed using the new two-phase voltages. Kalman filter is then applied to extract the frequency and phase angle of the fundamental component of the complex and actual recorded phasor. The proposed algorithm is tested on simulated data at different conditions for the three phase signals; noise free and balanced three phase signals, unbalanced three-phase system and harmonics contaminated three phase signals. It has been shown that the proposed filters with the proposed transformation are succeeded to estimate the signal frequency at off nominal, near nominal and at nominal frequency.