An Approximate and Practical Approach to Including Uncertainty Concepts in Generating Capacity Reliability Evaluation

Hamoud,; Billinton,

doi:10.1109/mper.1981.5511320

Cited by 9 publications

(2 citation statements)

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“…3) Approximate Method: A more computationally efficient approximate approach, which requires an iterative calculation for the probabilities only (i.e. not the covariances), is presented in [7]. This uses a Taylor expansion for small FOR errors to express the covariances in terms of the entries in the COPT (1) and the variance of the {R i }.…”

Section: A Fors Known Precisely: Capacity Outage Probability Tablementioning

confidence: 99%

“…Subsequent developments have included faster approximate methods based on Taylor expansions, for small data uncertainties, of the formulae for reliability indices, e.g. [5]- [7], and pp 63-67 of [3]. More recent work has extended this methodology to network reliability studies [8] and multi-area systems [9], and to the use of fuzzy set theory to model data errors [10].…”

Section: Introductionmentioning

confidence: 99%

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Non-Iterative Method for Modeling Systematic Data Errors in Power System Risk Assessment

Dent

Białek

2011

IEEE Trans. Power Syst.

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Publisher's copyright statement: c 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Additional information:Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Abstract-This paper provides a new framework for modelling uncertainty in the input data for power system risk calculations, and the error bars that this places on the results. Differently from previous work, systematic error in unit availability probabilities is considered as well as random error, and a closed-form expression is supplied for the error bars on the results. This closed-form expression reveals the relative contribution of different sources of error much more transparently than iterative methods. The new approach is demonstrated using the thermal units connected to the Great Britain transmission system. The availability probabilities used are generic type availabilities, published rounded to the nearest 5% by the system operator. Very wide error bars on the results of risk calculations result from the use of these probabilities; however, this is only revealed by modelling of the systematic error caused by the rounding. The approach is also used to investigate quantitatively the widely acknowledged view that comparing relative risks is a more robust use of simulated risk indices than stating absolute risk levels.

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Section: A Fors Known Precisely: Capacity Outage Probability Tablementioning

confidence: 99%