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Ekrem Gursoy
Advisor: Dagmar Niebur, Ph.D.
Abstract:
In the last couple of decades harmonics have become a major power quality problem in electric power systems. It is important to identify the harmonic sources in the system to solve and prevent the harmonic related problems. It is the original contribution of this thesis to model the harmonic load identification problem as a blind source separation task and to solve it using a statistical technique called Independent Component Analysis (ICA). Under non-sinusoidal conditions, harmonic voltage measurements are modeled as a linear combination of statistically independent harmonic current sources. This thesis demonstrates that ICA is well suited to estimate the harmonic current sources using a relatively small number of measurements and without knowledge of network topology and parameters. In addition to the harmonic source estimates, ICA also provides a rough estimate of the system admittance matrix. This matrix provides information for the location estimation of harmonic sources. A discussion of the sensitivity analysis of estimation algorithm on measurement noise, number of data points and measurements and the statistical independence are presented. The effectiveness of the proposed estimation algorithm is presented by computer simulations using several ICA methods and power system test cases.
Monday, April 9th, 2007 at 11 a.m.
Bossone 303
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