Distribution power system outage diagnosis based on root cause analysis

Document Type : Article

Authors

School of Electrical and Computer Engineering, Department of Engineering, Shiraz University, Zand Avenue, Shiraz, P.O. Box 71348-51154, Iran.

Abstract

This paper proposes data mining-based models to diagnose outage data in distribution power systems. In this work, outage data from a local distribution company is gathered and aligned with weather data. Then, a subset of features is selected to reduce the processing time and simplifying purposes. To increase the fairness of final models and to account for differences in misclassification cost, using a customized cost matrix is proposed. Two decision tree-based modeling algorithms are trained and tested. Results show the ability of the established models to diagnose the root cause of an outage fairly well. In addition, an ensemble of the decision tree-based models is built, which outperforms the other two models in almost all cases. Finally, applications of such models in decreasing outage duration and improving the reliability of the power distribution network are discussed.

Keywords

References

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Scientia Iranica
Volume 26, Special Issue on machine learning, data analytics, and advanced optimization techniques...
Transactions on Computer Science & Engineering and Electrical Engineering (D)
November and December 2019
Pages 3672-3680

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History

  • Receive Date: 07 August 2019
  • Revise Date: 01 September 2019
  • Accept Date: 07 October 2019

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