DocumentCode
1560010
Title
Including uncertainty in LOLE calculation using fuzzy set theory
Author
Kim, Jin-O ; Singh, Chanan
Author_Institution
Dept. of Electr. Eng., Hanyang Univ., Seoul, South Korea
Volume
17
Issue
1
fYear
2002
fDate
2/1/2002 12:00:00 AM
Firstpage
19
Lastpage
25
Abstract
This paper presents a conceptual possibilistic approach using fuzzy set theory to manage the uncertainties in the reliability input data of real power systems. In this paper, an algorithm is introduced to calculate the possibilistic reliability indices according to the degree of uncertainty in the given data. The probability distribution function can be transformed into an appropriate possibilistic representation using the probability-possibility consistency principle (PPCP) algorithm. In this algorithm, the transformation is performed by making a compromise between the transformation consistency and the human experience. Fuzzy classification theory is applied to reduce the number of load data points. The fuzzy classification method determines the closeness of load data points by assigning them to various clusters and then determining the distance between the clusters. The IEEE-RTS with 32-generating units is used to demonstrate the capability of the proposed algorithm
Keywords
fuzzy set theory; load (electric); power system analysis computing; power system faults; power system reliability; probability; IEEE-RTS; computer simulation; forced outage rate; fuzzy classification theory; fuzzy set theory; load data points; loss-of-load expectation; possibilistic approach; possibilistic reliability indices; power system reliability input data; probability distribution function; probability-possibility consistency principle algorithm; uncertainties management; Capacity planning; Clustering algorithms; Covariance matrix; Energy management; Fuzzy set theory; Power system management; Power system reliability; Random variables; Reliability theory; Uncertainty;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/59.982188
Filename
982188
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