DocumentCode :
3584357
Title :
A cluster distribution as a model for estimating high-order event probabilities in power systems
Author :
Chen, Qiming ; McCalley, James D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
fYear :
2004
Firstpage :
622
Lastpage :
628
Abstract :
We propose the use of the cluster distribution, derived from a negative binomial probability model, to estimate the probability of high order events in terms of number of lines outaged within a short time, useful in long term planning and also in short-term operational defense to such events. We use this model to fit statistical data gathered for a 30 year period for North America. The model is compared against the commonly used Poisson model and the Power Law model. Results indicate that the Poisson model underestimates the probability of higher order events while the Power Law model overestimates it. We use the strict Chi-square fitness test to compare the fitness of these three models and find that the cluster model is superior to the other two models for the data used in the study.
Keywords :
Poisson distribution; binomial distribution; power system faults; power system planning; statistical analysis; Chisquare fitness test; North America; Poisson model; Power Law model; cluster distribution; cluster model; contingency; negative binomial probability; power system planning; statistical data; Costs; North America; Power engineering and energy; Power engineering computing; Power system modeling; Power system planning; Power system reliability; Power system simulation; Probability; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2004 International Conference on
Print_ISBN :
0-9761319-1-9
Type :
conf
Filename :
1378759
Link To Document :
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