On-line measurement of low-frequency oscillations in power systems

This paper proposes modified Karhunen–Loeve transform with total least square estimation of signal parameters using rotational in-variance technique (MKLT-TLS-ESPRIT) to approximate the low-frequency oscillatory modes. MKLT decreases the impact of highly correlated additive colored Gaussian noise (ACGN) from the signal by differentiating the correlation matrix w.r.t from the final time instance. A quantitative study of the suggested method with other estimation methods is used to evaluate the effectiveness of the proposed method. Monte Carlo simulations with 50,000 runs are conducted to test the robustness of the estimation scheme for MKLT-TLS-ESPRIT. The evaluation of the efficiency of the proposed method in real-time perspective, the two-area system, and New England sixty-eight bus test system has been considered. The analysis shows that the suggested methodology correctly measures the interarea modes and lowers their mean and standard deviation to a minimum value.

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“…Let N1 be the recent power measurements received from the tie-line using PMU. It can be expressed by a signal and noise vector using (2).…”

Section: Steps To Implement Proposed Approach To Estimate the Power G...mentioning

confidence: 99%

“…But, this technique sufers with heavy numerical burden, inconsistency in parameter estimation, and large computational time. Ten, IAO modes need to be defned directly from the measured signal employing online techniques [2].…”

Section: Introductionmentioning

confidence: 99%

A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid

Samal

Khadanga

2023

Journal of Electrical and Computer Engineering

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“…Since observation matrix for oscillation is not observable, EM algorithm is employed and instead of maximizing (12), an averaged form of the log-likelihood function is maximized.…”

Section: Map Estimations Using Em-based Fb-klpfmentioning

confidence: 99%

Improved Recursive Electromechanical Oscillations Monitoring Scheme: A Novel Distributed Approach

Khalid¹,

Peng²

2015

IEEE Trans. Power Syst.

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This paper improves the existing Kalman-based technique for detecting electromechanical oscillations using Synchrophasor measurements. The novelty is the utilization of a distributed architecture to extract maximum a-posteriori (MAP) estimations of oscillatory parameters. This was achieved by an expectation maximization (EM) algorithm. To improve initial condition estimation, initial correlation information through a forward backward (FB) Kalman-like particle filter (KLPF) was integrated into the proposed scheme. Performance evaluation was conducted using IEEE New England 39-Bus system and Synchrophasor measurements collected from New Zealand Grid. The proposed method accurately extracted oscillatory parameters when the measurements were contaminated by continuous random small load fluctuations. The method also improved the capability of detecting multiple oscillations with similar frequencies.Index Terms-Distributed estimation, electromechanical oscillations, expectation maximization, forward-backward Kalman-like particle filter, inter-area oscillation, maximum a-posteriori, power system stability, synchrophasor.

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“…The states of the modern power systems are mainly monitored through phase measurement unit (PMU) based wide area measurement systems (WAMSs) [5]- [7]. Therefore, several measurement based methods for SSO analysis using PMU data have already been proposed in the literature.…”

Section: Introductionmentioning

confidence: 99%

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

G. Philip,

Jung,

Onen

2024

Journal of Modern Power Systems and Clean Energy

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This paper proposes an empirical wavelet transform (EWT) based method for identification and analysis of sub-synchronous oscillation (SSO) modes in the power system using phasor measurement unit (PMU) data. The phasors from PMUs are preprocessed to check for the presence of oscillations. If the presence is established, the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida algorithm. The superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest China. Results show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.

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On-line measurement of low-frequency oscillations in power systems

Cited by 17 publications

References 10 publications

A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid

A Novel Subspace Decomposition with Rotational Invariance Technique to Estimate Low-Frequency Oscillatory Modes of the Power Grid

Improved Recursive Electromechanical Oscillations Monitoring Scheme: A Novel Distributed Approach

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

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