Journal ArticleDOI
Identification and tracking of harmonic sources in a power system using a Kalman filter
Haili Ma,Adly A. Girgis +1 more
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TLDR
In this paper, 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 are solved using Kalman filtering.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.read more
Citations
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Neural-network-based signature recognition for harmonic source identification
TL;DR: A neural-network (NN)-based approach to nonintrusive harmonic source identification and MLP was found to be the best signature identification method because of its low computational requirements and ability to extract the information necessary for highly accurate device identification.
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Power quality following deregulation
TL;DR: In this article, the authors present methods available in these areas to achieve specified levels of power quality in the deregulated environment, which will affect the standards, system simulation and monitoring tools.
Journal ArticleDOI
An adaptive Kalman filter for dynamic harmonic state estimation and harmonic injection tracking
TL;DR: In this paper, an adaptive Kalman filter method for dynamic harmonic state estimation and harmonic injection tracking is proposed, which models the system as a linear frequency independent state model and does not require an exact knowledge of the noise covariance matrix.
Journal ArticleDOI
Harmonics estimation in emerging power system: Key issues and challenges
TL;DR: In this article, several methods of power system harmonics estimation are critically reviewed and classified based on the type of analysis tool and applications and the key issues and challenges in harmonics estimations are highlighted.
Journal ArticleDOI
Extended Real Model of Kalman Filter for Time-Varying Harmonics Estimation
TL;DR: An extended real model of Kalman filter combined with a resetting mechanism for accurately tracking time-varying harmonic components of power signals is presented in this article, where the usefulness of the proposed algorithm is demonstrated by a simple laboratory setup with LabVIEW program and the dedicated hardware for harmonics monitoring.
References
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Journal ArticleDOI
A digital recursive measurement scheme for online tracking of power system harmonics
TL;DR: In this article, an optimal measurement scheme for tracking the harmonics in power system voltage and current waveforms is presented, which is based on Kalman filtering theory for the optimal estimation of the parameters of time-varying harmonics.
Journal ArticleDOI
Identification of harmonic sources by a state estimation technique
TL;DR: In this paper, a reverse power flow procedure is described to identify the sources of harmonic signals in electric power systems, where line and bus data at several points in the network are used with a least-squares estimator to calculate the injection spectrum at buses suspected of being harmonic sources.
Journal ArticleDOI
Optimal Estimation Of Voltage Phasors And Frequency Deviation Using Linear And Non-Linear Kalman Filtering: Theory And Limitations
TL;DR: In this paper, two techniques for optimal tracking of power system voltage phasors and frequency deviation were presented, one based on a two-state linear Kalman filter model and the other based on three-state extended Kalman filters.
Journal ArticleDOI
Dynamic state estimation of power system harmonics using Kalman filter methodology
H.M. Beides,Gerald T. Heydt +1 more
TL;DR: In this paper, a Kalman filter is used to obtain the optimal estimate of the power system harmonic content and the effect of load variation over a one day cycle on power system harmonics and standard are presented.
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