Title :
Identification and tracking of harmonic sources in a power system using a Kalman filter
Author :
Ma, Haili ; Girgis, Adly A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
fDate :
7/1/1996 12:00:00 AM
Abstract :
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
Keywords :
Kalman filters; covariance analysis; covariance matrices; distribution networks; identification; power system harmonics; power system measurement; Kalman filter; harmonic measurements; harmonic meters location; harmonic source injection; harmonic sources identification; harmonic sources tracking; matrices; noisy harmonic measurements; optimal dynamic estimates; power distribution system; power system; system error covariance analysis; unbalanced three-phase power systems; Error analysis; Filtering; Harmonic analysis; Kalman filters; Position measurement; Power harmonic filters; Power system analysis computing; Power system dynamics; Power system harmonics; Power system simulation;
Journal_Title :
Power Delivery, IEEE Transactions on