Title :
Application of Fuzzy Clustering Technique to Reduce the Load Data in Reliability Evaluation of Restructured Power Systems
Author :
Viswanath, P.A. ; Goel, L. ; Wang, P.
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia
Abstract :
This paper presents the application of fuzzy clustering technique on large load data to greatly reduce calculations in reliability evaluation of restructured power systems. The method involves: first grouping a large load data into few clusters, secondly calculating partial membership value of each load point in each cluster, thirdly calculating reliability indices for each cluster and finally, expressing the reliability indices at each load point in terms of the reliability index of the cluster and the membership value that the load point has in that cluster. A non-sequential Monte Carlo simulation technique based on this framework has been proposed to evaluate the customer reliability of restructured power systems.
Keywords :
Monte Carlo methods; fuzzy set theory; pattern clustering; power markets; power system reliability; customer reliability; fuzzy clustering technique; load data; nonsequential Monte Carlo simulation technique; power system reliability; reliability evaluation; restructured power systems; Clustering algorithms; Contingency management; Fuzzy systems; Hybrid power systems; ISO; Power generation; Power system analysis computing; Power system modeling; Power system reliability; Sampling methods;
Conference_Titel :
Emerging Trends in Engineering and Technology (ICETET), 2009 2nd International Conference on
Conference_Location :
Nagpur
Print_ISBN :
978-1-4244-5250-7
Electronic_ISBN :
978-0-7695-3884-6
DOI :
10.1109/ICETET.2009.37
