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Application of Monte Carlo Simulation to Well-Being Analysis of Large Composite Power Systems

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3 Author(s)
Leite da Silva, A.M. ; Power Syst. Eng. Group, Fed. Univ., Itajuba ; Resende, L.C. ; Manso, L.A.F.

This paper presents a new methodology to evaluating the well-being indices of large composite generation and transmission systems. A well-being framework is used to classify the system states into healthy, marginal and at risk, according to a pre-defined deterministic criterion. In order to combine deterministic and probabilistic concepts, the proposed methodology uses a non-sequential Monte Carlo simulation, a multi-level non-aggregate Markov load model and test functions to estimate the well-being indices for the system and load buses. Moreover, a network reduction is also proposed to find an equivalent well-being framework suitable to practical large power systems. Case studies on an IEEE standard system and on a configuration of the Brazilian network are presented and discussed

Published in:

Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on

Date of Conference:

11-15 June 2006