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Identification of Inter-Area Oscillations Using Zolotarev Polynomial Based Filter Bank with Eigen Realization Algorithm
Published in Institute of Electrical and Electronics Engineers Inc.
2016
Volume: 31
   
Issue: 6
Pages: 4650 - 4659
Abstract
Inter-area oscillations in power systems needs to be monitored and accurate estimation of frequency and damping of the oscillations in real time is vital as they provide considerable insight into system stability. Zolotarev polynomial based filter bank (ZPBFB) is proposed for decomposing the PMU signals into monocomponents. Modal frequency and damping are obtained from the decomposed monocomponent signals through eigen realization algorithm (ERA). The salient property of ZPBFB lies in signal decomposition with sum of decomposed signals produced by filter bank, without oversampling, is an exact replica of input signal with delay. A narrow bandwidth of 0.1 Hz is achieved in the frequency range of 0 to 1 Hz with ZPBFB. The robustness of the proposed method to noise is demonstrated using Monte Carlo simulations. The proposed ZPBFB and cosine modulated filter bank (CMFB) are implemented on two-area test system and 16-machine, 68-bus system and the performances are compared. The efficacy of the proposed method is also demonstrated on three real time signals recorded by wide area frequency measurement system (WAFMS) at 3 locations in India on November 30, 2011. © 1969-2012 IEEE.
About the journal
JournalData powered by TypesetIEEE Transactions on Power Systems
PublisherData powered by TypesetInstitute of Electrical and Electronics Engineers Inc.
ISSN08858950
Open AccessNo
Concepts (20)
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    Algorithms
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    Bandpass filters
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    Circuit oscillations
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    Damping
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    ELECTRIC FREQUENCY MEASUREMENT
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    Filter banks
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    Frequency estimation
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    Intelligent systems
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    Monte carlo methods
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    Real time systems
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    System stability
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    Accurate estimation
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    COSINE MODULATED FILTER BANKS
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    EIGEN REALIZATION
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    FREQUENCY MEASUREMENT SYSTEMS
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    INTER-AREA OSCILLATIONS
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    MONO-COMPONENT SIGNAL
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    POLYNOMIAL BASED FILTERS
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    SIGNAL DECOMPOSITION
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    Signal processing