2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) 2020
DOI: 10.1109/pmaps47429.2020.9183660
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Probabilistic Multi-Stability Assessment in Power Systems with Uncertain Wind Generation

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Cited by 4 publications
(2 citation statements)
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“…Given that renewable energy sources contribute very little to conventional power systems, this approximation is valid (Kazeminejad et al 2020). Monte Carlo simulation (MCS) is a popular technique for modeling various system complexities for probability voltage stability assessment (Mochamad et al 2020). A method based on cumulates is suggested for saddle node bifurcation point detection, taking load forecast errors into account.…”
Section: 𝐼𝑀𝑀(πœ‡mentioning
confidence: 99%
“…Given that renewable energy sources contribute very little to conventional power systems, this approximation is valid (Kazeminejad et al 2020). Monte Carlo simulation (MCS) is a popular technique for modeling various system complexities for probability voltage stability assessment (Mochamad et al 2020). A method based on cumulates is suggested for saddle node bifurcation point detection, taking load forecast errors into account.…”
Section: 𝐼𝑀𝑀(πœ‡mentioning
confidence: 99%
“…This rapid growth in power electronic systems has attracted considerable attention and concern from power system researchers and engineers, especially regarding the robust and reliable operation of these reformed systems due to their fast dynamics, wide timescale However, so far, probabilistic assessment has not been widely used in modern power system studies except for specific topics, such as reliability assessment (adequacy and security) [35][36][37], lifetime estimation [38], and efficiency calculation [39]. In [31][32][33][34], probabilistic-transient and small-signal stability assessments have been performed in order to consider the impact of load variations, the stochastic generation of renewable energy sources, and other system disturbances. However, stability analysis is based on rotor-angle stability analysis that was developed for low-frequency stability analysis of traditional power systems.…”
Section: Introductionmentioning
confidence: 99%