Dynamic Power Systems Phasor Estimation Using Kalman Filter Algorithms
In the electrical power system, the accuracy of phasor estimation represents essential and critical issue due to the dependability of many fields on the characteristic of the estimated signals. Therefore, several algorithms have been suggested to estimate the main aspects of these signals. This paper presents a comparative evaluation of dynamic phasor estimation algorithms, namely the linear Kalman and extended Kalman filter. Many tests have been made on the dynamic filters were developed in the Simulink environment of MATLAB, The tests include amplitude step, phase step, frequency step, total vector error and computation time. Test and simulation results are provided to highlight each algorithm suitability and limitations to estimate the phasor of the power system.
KeywordsKalman Filters Phasor estimation Protection Relays WAMS Discrete Fourier Transformation
- 5.Yang, F., Meliopoulos, A.S., Cokkinides, G.J., Dam, Q.B.: Effects of protection system hidden failures on bulk power system reliability. In: 2006 38th North American Power Symposium, NAPS 2006, pp. 517–523 (2006)Google Scholar
- 6.Mansour, Y.: Voltage stability of power systems: concepts, analytical tools, and industry experience. IEEE Special Publication (1990)Google Scholar
- 13.UmaMageswari, A., Ignatious, J.J., Vinodha, R.: A comparitive study of Kalman filter, extended Kalman filter and unscented Kalman filter for harmonic analysis of the non-stationary signals. Int. J. Sci. Eng. Res. 3(7), 1–9 (2012)Google Scholar
- 16.Haykin, S.: Kalman Filtering and Neural Networks, vol. 47. Wiley, Hoboken (2004)Google Scholar
- 18.IEEE Standard for Synchrophasors for Power Systems. IEEE Std C37.118-2005 (Revision of IEEE Std 1344-1995), pp. 0_1–57 (2006)Google Scholar