An adaptive scheme to improve Prony's method performance to estimate signal parameters of power system oscillations

This work introduces a new methodology based on Neural Networks (NNs) and Prony's method to estimate the signal parameters during power oscillations related to transient phenomena caused by severe perturbations. Power system dynamic analysis becomes essential to establish reliability indices un...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-1
Main Authors: Tapia-Olvera, Ruben, Guillen, Daniel, Beltran-Carbajal, Francisco, Castro, Luis M.
Format: Article
Language:English
Subjects:
Adaptive order
Artificial neural networks
Damping
Estimation
Fast Fourier transformations
Fourier transforms
Frequency estimation
Haar transformations
Neural networks
Oscillations
Oscillators
Parameter estimation
Performance indices
Perturbation
Power oscillations
Power system stability
Prony's method
Reliability analysis
Reliability aspects
Stability criteria
Transient analysis
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Summary:This work introduces a new methodology based on Neural Networks (NNs) and Prony's method to estimate the signal parameters during power oscillations related to transient phenomena caused by severe perturbations. Power system dynamic analysis becomes essential to establish reliability indices under critical conditions; these indices are commonly based on signal parameters estimated at different points throughout the power system. In this context, the proposed approach offers several advantages due to the adaptability of NNs. The proposed formulation is firstly analyzed with a signal model with different oscillating components. This technique is validated for a wide range of conditions, where the results show good accuracy to carry out the estimation of the signal parameters such as frequency and damping. Additionally, the proposed method is validated using a multi-machine power system with four synchronous generators considering different operating conditions that result in power oscillations; comparison results against the fast Fourier transform (FFT), conventional Prony's method, Matrix Pencil method, and Prony combined with Haar transform are included to prove the effectiveness of the proposed approach. Quantitative indexes which exhibit the performance of the proposal are presented to duly demonstrate the evolution of new adaptive scheme.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2022.3191721