Application of Bayesian method for electrical power system transient stability assessment

Augutis, Juozas; Žutautaitė, Inga; Radziukynas, Virginijus; Krikštolaitis, Ričardas; Kadisa, Sigitas

doi:10.1016/j.ijepes.2012.04.054

Cited by 14 publications

(9 citation statements)

References 24 publications

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“…the values of indicators depends on time t. Classical application of BM is not correct in this case, because observations obtained in different time moments represent the other state of the indicators. The modified application of BA for the calculation estimates of parameters of non-stationary process mathematical models is presented in research paper [8].…”

Section: Stochastic Initial Conditions Of Differential Equations Systemmentioning

confidence: 99%

Dynamic model for energy security level assessment

Augutis¹,

Pe²,

iulyt³

et al. 2012

Risk Analysis VIII

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Effective functioning of the energy sector is very important for the economy of every modern state. Thus, energy security is an inseparable part of the total economic security of the state. Energy security indicators were constructed for the investigation of the Lithuanian energy security level. The purpose of the paper is to construct a dynamic model for energy security level assessment. Dynamic model of indicators will enable us to forecast the Lithuanian energy security level according to different factors, such as building of liquefied natural gas (LNG) terminal, power interconnections between Lithuania and Poland (LitPolLink), etc. Since technical parameters of new objects are not exactly known, these uncertainties should be reflected in the initial conditions of a differential equations system. Thus, in such conditions, the values of indicators are random variables. The paper presents a model of dynamic indicators and pilot calculations.

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Section: Stochastic Initial Conditions Of Differential Equations Systemmentioning

confidence: 99%

Dynamic model for energy security level assessment

Augutis¹,

Pe²,

iulyt³

et al. 2012

Risk Analysis VIII

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“…In Farantatos, by using real‐time estimated dynamic equivalent of the generator based on Lyapunov direct method, a transient stability monitoring scheme is presented. In Augutis, a critical postfault time assessment methodology has been presented for transient stability assessment. In this paper based on the Bayesian approach, a dependency function of the generators with estimated characteristics has been presented.…”

Section: Introductionmentioning

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

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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.

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“…[3] showed that employing Bayesian methods could enhance transmission grid risk analysis. [4] used Bayesian method for electrical power system transient stability assessment. [5] developed a Bayesian belief network model for electrical load demand.…”

Section: Introductionmentioning

confidence: 99%

Availability Assessment of Electric Power based on Switch Reliability Modelling with Dynamic Bayesian Networks: Case Study of Electrical Distribution Networks

Lakehal¹,

Ghemari²

2015

JMSS

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Abstract:As a generalization of the successful hidden Markov models, Dynamic Bayesian Networks (DBNs) are a natural basis for the general temporal action interpretation task. This document provides a conditional probabilistic approach to analyze the energy availability in electrical distribution networks by using Bayesian networks (BN). Firstly a static BN modelling is presented to show the influence of the switch behaviour on the energy availability. Then, the dynamic behaviour of the switch is cared by switch reliability modelling using DBN which permits to predict the energy availability. The prediction by DBNs discussed in the case study of this paper gives a strong contribution on electrical network supervisory control and it can also be applied to transportation networks.

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Application of Bayesian method for electrical power system transient stability assessment

Cited by 14 publications

References 24 publications

Dynamic model for energy security level assessment

Dynamic model for energy security level assessment

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

Availability Assessment of Electric Power based on Switch Reliability Modelling with Dynamic Bayesian Networks: Case Study of Electrical Distribution Networks

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