Including uncertainty in LOLE calculation using fuzzy set theory Academic Article

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.

authors

• Singh, Chanan

published proceedings

• IEEE TRANSACTIONS ON POWER SYSTEMS

author list (cited authors)

• Kim, J. O., & Singh, C.

citation count

• 37

publication date

• February 2002

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Forced Outage Rate
• Fuzzy Clustering
• Loss-of-load Expectation
• Probability-possibility Consistency Principle

Digital Object Identifier (DOI)

• 10.1109/59.982188

start page

• 19

end page

• 25

volume

• 17

issue

• 1

URL

• http://dx.doi.org/10.1109/59.982188