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• W4323925008 abstract "Abstract Deteriorated power system components have a higher probability of failure than new components. Still, the reliability of supply analyses traditionally models all components of the same type with the same probability of failure, and thus neglects the effect of deteriorated components. This paper presents a methodology to integrate a condition‐dependent component probability of failure model into a power system reliability analysis. The component state is described by a semi‐Markov process, and the paper shows how this, under reasonable assumptions, can be approximated by a Markov process. The Markov assumption simplifies the analysis and allows the model to include preventive retirement and be calibrated to statistical data. A case study using statistical data for Norwegian power transformers shows that, in the Norwegian power system, the proportion of failures that are due to the poor condition is small, partly due to the common strategy of preventive retirement. However, if the condition of the transformers were worse, the impact of poor conditions can be considerable. The methodology further enables the identification of the transformers that contribute most to the risk to the reliability of supply. The paper thus highlights the importance of accounting for the component condition in strategic decisions such as long‐term renewal planning" @default.
• W4323925008 created "2023-03-12" @default.
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• W4323925008 date "2023-03-10" @default.
• W4323925008 modified "2023-10-18" @default.
• W4323925008 title "Accounting for component condition and preventive retirement in power system reliability analyses" @default.
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• W4323925008 doi "https://doi.org/10.1049/gtd2.12761" @default.
• W4323925008 hasPublicationYear "2023" @default.
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