Identification and tracking of harmonic sources in a power system using a Kalman filter

• Published in: IEEE transactions on power delivery Vol. 11; no. 3; pp. 1659 - 1665
• Main Authors: Haili Ma, Girgis, A.A.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY IEEE 01.07.1996; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Disturbances. Regulation. Protection; Electrical engineering. Electrical power engineering; Electrical power engineering; Error analysis; Exact sciences and technology; Filtering; Harmonic analysis; Kalman filters; Position measurement; Power harmonic filters; Power networks and lines; Power system analysis computing; Power system dynamics; Power system harmonics; Power system simulation; Measuring instrument; Harmonic; Mathematical formula; Electrical network; Simulation; Kalman filtering; Identification; Perturbation; Optimal estimation; Localization
• ISSN: 0885-8977; 1937-4208
• DOI: 10.1109/61.517531

In this paper, two problems have been addressed on harmonic sources identification: the optimal locations of a limited number of harmonic meters and the optimal dynamic estimates of harmonic source locations and their injections in unbalanced three-phase power systems. Kalman filtering is used to solve these problems. System error covariance analysis by the Kalman filter associated with a harmonic injection estimate determines the optimal arrangement of limited harmonic meters. Based on the optimally-arranged harmonic metering locations, the Kalman filter then yields the optimal dynamic estimates of harmonic injections with a few noisy harmonic measurements. The method is dynamic and has the capability of identifying, analyzing and tracking each harmonic injection at all buses in unbalanced three-phase power systems. Actual recorded harmonic measurements and simulated data in a power distribution system are provided to prove the efficiency of this approach.