NDLI: Adaptive master–slave unscented Kalman filter for grid voltage frequency estimation

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Volume 12 (2018) : Issue 3, May

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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Adaptive master–slave unscented Kalman filter for grid voltage frequency estimation

Content Provider	IET Digital Library
Author	Muñoz, Juan P. Magaña, Mario E. Sanchez, Eduardo Cotilla
Abstract	The frequency of the grid voltage is a time-varying parameter caused by mismatches between power generation and power consumption. In fact, the fundamental frequency decreases when large loads are connected to the system or when a large generation source goes offline. The opposite holds true for an increase in the fundamental frequency, e.g. when generation exceeds consumption. Hence, in order to protect a power system against loss of synchronism, under-frequency relaying, and power system stabilisation, accurate frequency estimation is necessary. This study proposes an adaptive algorithm based on a master–slave unscented Kalman filter (UKF) configuration to estimate both the voltage frequency and the measurement noise. Specifically, the master UKF uses the strong tracking filter condition to improve tracking accuracy, speed of convergence, and to desensitise the filter from initial conditions. The slave UKF uses the master UKF innovation to estimate the measurement noise covariance. The proposed approach addresses the tracking weaknesses of other frequency estimation algorithms when the frequency of the grid voltage waveform changes abruptly. Algorithm performance is measured through computer simulation.
Starting Page	496
Ending Page	505
Page Count	10
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 4, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0199
Journal	IET Signal Processing
Publisher Date	2017-12-05
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Algorithm Adaptive Master–slave Unscented Kalman Filter Convergence Filter And Other Network Frequency Estimation Fundamental Frequency Grid Voltage Frequency Estimation Grid Voltage Waveform Kalman Filter Master UKF Mathematical Analysis Measurement Error Measurement Noise Covariance Measurement Uncertainty Nonlinear Filter Power Consumption Power Generation Power System Control Power System Parameter Estimation Power System Stabilisation Power System Stability Statistics Time-varying Parameter Tracking Accuracy Tracking Filter Tracking Filter Condition Under-frequency Relaying Waveform Analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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