This paper presents a Monte Carlo approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. The uncertainties considered include both generation and demand in power systems, though others, such as parameter changes of network components, can be added as well. Probabilistic models of these uncertainties are constructed considering their characteristics. Subsequently, probabilistic small signal stability assessment of the power system is carried out based on eigenvalue analysis via Monte Carlo Simulation. The proposed method is tested by analysing the eigenvalues of two benchmark systems, where stable, unstable and oscillation modes are identified in the probabilistic context. In addition, local and inter-area modes of electro-mechanical oscillation are classified. Relevant discussion of stability enhancement using the proposed approach has been presented as well. The proposed method aims at providing a comprehensive characterization of system stability which can be very helpful in applications, such as system operation and expansion planning in the deregulation with many uncertainties.
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Xu et al. (2005) studied this question.
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