A new approach for online coherency identification in power systems based on correlation characteristics of generators rotor oscillations

Aghamohammadi, Mohammad Reza; Tabandeh, Saleh

doi:10.1016/j.ijepes.2016.04.019

Cited by 54 publications

(43 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, by measuring voltage and current phasor at generator terminal and having generator transient reactance ( X'd ), it is possible to estimate rotor angle ( δ ) and rotor speed ( ω ) deviations. The details of related calculations can be found in Aghamohammadi . To find the best feature for training Bayesian, the following steps are taken.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent prediction of out-of-step condition on synchronous generators because of transient instability crisis

Zare

Alinejad‐Beromi

Yaghobi

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary This paper presents an adaptive scheme for predicting out‐of‐step (OOS) condition of synchronous generator based on the Bayesian technique. The proposed scheme performs as an intelligent OOS method for synchronous generators from which by using training variables, the tripping signals are estimated. For classifying target classes between stable and OOS conditions, a series of measurements are derived under various fault scenarios including topological and operational disturbances. The tripping signals are estimated by using feature selection technique based on the Bayesian technique. In this procedure, the data of input variables and corresponding output target classes are implemented as input‐output pair data for Bayesian training and testing. For this propose, the ability of the OOS protective scheme is examined for a number of unseen samples in working mode. The proposed approach is applied on IEEE 39‐bus test system from which by using trained variables, the tripping signals are estimated online. Furthermore, to evaluate the proposed protective scheme in real‐time environment, a 2‐machine experimental case is used to assess the effectiveness of the proposed scheme. The results show a promising performance of proposed protective scheme for proper estimating of tripping signals.

show abstract

Section: The Proposed Algorithmmentioning

confidence: 99%

“…The details of related calculations can be found in Aghamohammadi. 43 To find the best feature for training Bayesian, the following steps are taken.…”

Section: Feature Selectionmentioning

confidence: 99%

Intelligent prediction of out-of-step condition on synchronous generators because of transient instability crisis

Zare

Alinejad‐Beromi

Yaghobi

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…between two independent variables or between an independent and a dependent variable). It used to describe the strength and direction of a linear relationship between two variables . The correlation measure just tells us the existence of the association between x and y , but it does not show us the shape of the relationship or give any chance to predict one variable from the other.…”

Section: Correlation Coefficient – Basic Theorymentioning

confidence: 99%

A correlation coefficient‐based algorithm for fault detection and classification in a power transmission line

Musa

et al. 2018

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

This paper presents a new algorithm for fault detection and classification in a power transmission line. The fundamental idea of the proposed algorithm is the calculation of the correlation coefficient (CC) between the current signal of each phase of the three-phase system and its reference value. The following rule makes the decision of detecting and classifying the fault condition: when the system is running under healthy condition, the correlation between the current signal of each phase and its reference value is very strong; when the system is in faulty condition, the correlation between the current signal of each phase and its reference value is low compared to that in the healthy condition. The new algorithm is applied to a power transmission line model established in PSCAD/EMTDC. Different fault circumstances such as different inception times, different fault resistances, and different locations have been verified. Additionally, far-end faults with high resistance, faults occurring near a terminal, faults considering variable loading angle, and faults in the presence of noise are easily detected by the proposed method. For each possible scenario of fault, the proposed algorithm requires only the three-phase current measurement of the local measurement unit. The results show satisfactory performance in most cases.

show abstract

“…The correlation-based method proposed in [24] was carried out as a benchmark. It calculates the correlation coefficient for each pair of generators and splits them based on the average correlation value.…”

Section: Fig 5 Formation Of Two Islandsmentioning

confidence: 99%

“…The proposed algorithm uses generators rotor angles, estimated through PMU measurements, based on which optimal cut-set can be determined with minimum circuit breaker option and load shedding. The proposed approach has been demonstrated on the IEEE 39-bus system against correlation based [24] and community detection based [2] islanding approaches. Time domain simulations are used to validate and demonstrate the effectiveness of the proposed methodology in minimizing impacts of cascading outages and system-wide blackouts.…”

Section: Iintroductionmentioning

confidence: 99%

Online coherence identification using dynamic time warping for controlled islanding

Banna

Shi

et al. 2018

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

Controlled islanding is considered to be the last countermeasure to prevent system-wide blackouts in case of cascading failures. It splits the system into self-sustained islands to maintain transient stability at the expense of possible loss of load. Generator coherence identification is critical to controlled islanding scheme as it helps identify the optimal cutset to maintain system transient stability. This paper presents a novel approach for online generator coherency identification using phasor measurement unit (PMU) data and dynamic time warping (DTW). Results from the coherence identification are used to further cluster non-generator buses using spectral clustering with the objective of minimizing power flow disruption. The proposed approach is validated and compared to existing methods on the IEEE 39-bus system, through which its advantages are demonstrated.

show abstract

A new approach for online coherency identification in power systems based on correlation characteristics of generators rotor oscillations

Cited by 54 publications

References 28 publications

Intelligent prediction of out-of-step condition on synchronous generators because of transient instability crisis

Intelligent prediction of out-of-step condition on synchronous generators because of transient instability crisis

A correlation coefficient‐based algorithm for fault detection and classification in a power transmission line

Online coherence identification using dynamic time warping for controlled islanding

Contact Info

Product

Resources

About