| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 399953 | International Journal of Electrical Power & Energy Systems | 2012 | 7 Pages |
The use of probability distribution functions to describe reliability-worth input parameters is fairly new compared to using average values. Reliability-worth indices of power systems are frequently calculated as average values and convey little information about risk. In this paper beta probability distribution function was used to model time-dependent customer interruption costs as an input parameter to reliability-worth analyses of power systems. Time-sequential Monte-Carlo simulation technique that can handle time dependence of the input parameters was employed in the analysis. The results revealed that more information can be derived from the reliability-worth indices when probability distributions are used to describe the reliability-worth input and output parameters.
► We model reliability-worth input and output parameters using a beta distribution function. ► Time variation of customer interruption cost was included in the analysis. ► A time sequential Monte-Carlo simulation technique was used to perform the reliability-worth analysis. ► We examine changes in the reliability-worth index for different risk levels. ► The use of probability distribution functions enhance the interpretation of the index computed.
