Power System Reliability Assessment using the Weibull-Markov Model

This Licenciate Thesis introduces an alternative stochastic model for performing reliability assessment calculations in electric power systems. This new model has been developed because the commonly used “homogenous Markov” model cannot be used to calculate cost parameters accurately. Yet, the current market developments lead to an increasing demand for costoriented reliability assessment. The proposed alternative model, which was given the name “Weibull-Markov Model”, has been implemented and used in a commercial reliability assessment program with success. The use of the new model has proven not to cause any relevant slowing down of the calculation process, and yet to deliver reliability cost indices at the same time. Additional reliability calculations for cost calculations therefore are felt not to be required anymore. A very important quality of the Weibull-Markov model is that it is 100% backwards compatible with the homogenous Markov model. This means that the reliability data that has been gathered to great costs and effort in the past, can still be used in the new calculations. The Weibull-Markov model provides for a so-called shape parameter with wich an existing homogenous Markov model can be adjusted to bring it closer to the measured data without actually changing the original data. More research however will be needed to test the Weibull-Markov model further for its merits and limits.

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