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PREDICTION OF WEATHER-RELATED FAILURES OF OVERHEAD DISTRIBUTION FEEDERS

Published online by Cambridge University Press:  12 December 2005

Yujia Zhou ,
Anil Pahwa  and
Sanjoy Das
Yujia Zhou
Affiliation:
Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506-5204, E-mail: Yujia.Zhou@us.kema.com; pahwa@ksu.edu; sdas@ksu.edu
Anil Pahwa
Affiliation:
Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506-5204, E-mail: Yujia.Zhou@us.kema.com; pahwa@ksu.edu; sdas@ksu.edu
Sanjoy Das
Affiliation:
Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506-5204, E-mail: Yujia.Zhou@us.kema.com; pahwa@ksu.edu; sdas@ksu.edu
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Abstract

This article presents two methods for predicting weather-related overhead distribution feeder failures. The first model is based on linear regression, which uses a regression function to determine the correlation between the weather factors and overhead feeder failures. The second method is based on a one-layer Bayesian network, which uses conditional probabilities to model the correlation. Both methods are discussed and followed by tests to assess their performance. The results obtained using these methods are discussed and compared.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 20 , Issue 1 , January 2006 , pp. 117 - 125
Copyright
© 2006 Cambridge University Press

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References

REFERENCES

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