NDLI: Combination of Kalman Filter and Least-Error Square Techniques in Power System

Content Provider	IEEE Xplore Digital Library
Author	Zadeh, R.A. Ghosh, A. Ledwich, G.
Copyright Year	1986
Abstract	An algorithm based on the concept of combining Kalman filter and least-error square (LES) techniques is proposed in this paper. The algorithm is intended to estimate signal attributes like amplitude, frequency and phase angle in the online mode. This technique can be used in protection relays, digital AVRs, DGs, DSTATCOMs, FACTS, and other power electronics applications. The Kalman filter is modified to operate on a fictitious input signal and provides precise estimation results insensitive to noise and other disturbances. At the same time, the LES system has been arranged to operate in critical transient cases to compensate the delay and inaccuracy identified because of the response of the standard Kalman filter. Practical considerations such as the effect of noise, higher order harmonics, and computational issues of the algorithm are considered and tested in the paper. Several computer simulations and a laboratory test are presented to highlight the usefulness of the proposed method. Simulation results show that the proposed technique can simultaneously estimate the signal attributes, even if it is highly distorted due to the presence of nonlinear loads and noise.
Sponsorship	IEEE Power Engineering Society
Starting Page	2868
Ending Page	2880
Page Count	13
File Size	836592
File Format	PDF
ISSN	08858977
Volume Number	25
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power systems Power system protection Power system relaying Frequency estimation Testing Amplitude estimation Phase estimation Digital relays Protective relaying Power electronics phase angle estimation frequency estimation harmonics Kalman filtering least-error square noise nonlinear loads
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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