DocumentCode :
2876595
Title :
New advances in integrating fuzzy data in Monte Carlo simulation to evaluate reliability indices of composite power systems
Author :
Saraiva, Joao Tomé ; Sousa, A.V.
Author_Institution :
FEUP/DEEC, INESC, Porto, Portugal
Volume :
2
fYear :
1998
fDate :
18-20 May 1998
Firstpage :
1084
Abstract :
In this paper, several concepts related to the application of Monte Carlo simulation to evaluate the reliability indices of composite power systems are reviewed. In the sequence of previous papers, one integrates in the Monte Carlo simulation a DC fuzzy optimal power flow model to cope with uncertainties in peak loads. This general framework is now enhanced as one can specify fuzzy load duration curves, uncertainties in repair and failure rates and can adopt either nonchronological or chronological sampling strategies. This package can thus be used to evaluate the impact in the expected values of power and energy not supplied of uncertainties affecting several variables and parameters
Keywords :
Monte Carlo methods; failure analysis; fuzzy set theory; load flow; power system analysis computing; power system reliability; DC fuzzy optimal power flow model; Monte Carlo simulation; composite power systems; computer simulation; energy not supplied; failure rates; fuzzy data integration; fuzzy load duration curves; peak load uncertainties; power not supplied; reliability indices evaluation; repair rates; sampling strategies; Fuzzy systems; Load flow; Packaging; Power generation; Power system modeling; Power system planning; Power system reliability; Power system simulation; Sampling methods; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrotechnical Conference, 1998. MELECON 98., 9th Mediterranean
Conference_Location :
Tel-Aviv
Print_ISBN :
0-7803-3879-0
Type :
conf
DOI :
10.1109/MELCON.1998.699399
Filename :
699399
Link To Document :
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