A Bayesian inference approach is proposed for power systems transient stability assessment. Such assessment is crucial for modern power systems, which must often operate close to their stability limits, and are facing increasing levels of uncertainty. In particular, the estimation of the transient instability probability of a system is discussed in the paper, based upon Bayes estimation of the parameters of the basic random variables (e.g. the expected values of the clearing times). A large series of numerical simulations show that the proposed estimation method constitutes a very efficient method. Moreover, other numerous simulations have been performed for the purpose of a robustness analysis, showing that the methodology efficiency appears to hold also when departing from the assumptions made on prior parameter distributions and also on basic model distributions.

A Bayes Inference Method for Probabilistic Transient Stability Assessment of Power Systems

CHIODO, ELIO
2013

Abstract

A Bayesian inference approach is proposed for power systems transient stability assessment. Such assessment is crucial for modern power systems, which must often operate close to their stability limits, and are facing increasing levels of uncertainty. In particular, the estimation of the transient instability probability of a system is discussed in the paper, based upon Bayes estimation of the parameters of the basic random variables (e.g. the expected values of the clearing times). A large series of numerical simulations show that the proposed estimation method constitutes a very efficient method. Moreover, other numerous simulations have been performed for the purpose of a robustness analysis, showing that the methodology efficiency appears to hold also when departing from the assumptions made on prior parameter distributions and also on basic model distributions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/564276
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