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This paper presents a Monte-Carlo algorithm considering loads defined by fuzzy numbers. In this methodology states are sampled according to the probabilistic models governing the life cycle of system components while fuzzy concepts are used to model uncertainty related to future load behavior. This model can be used to evaluate generation/transmission power system reliability for long term planning studies as one uses the more adequate uncertainty models for each type of data. For each sampled state a fuzzy optimal power flow is run so that one builds its power nor supplied membership function. The paper proposes new indices reflecting the integration of probabilistic models and fuzzy concepts and discusses the application of variance reduction techniques if loads are defined by fuzzy numbers. A case-study based on the IEEE 30 bus system illustrates this methodology
Published in:
Power Systems, IEEE Transactions on
(Volume:11
,
Issue:
2
)
Date of Publication: May 1996
- Page(s):
- 690 - 695
- ISSN :
- 0885-8950
- INSPEC Accession Number:
- 5289324
- Digital Object Identifier :
- 10.1109/59.496140
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- May 1996
- Sponsored by :
- IEEE Power & Energy Society
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