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Information Journal Paper

Title

Distribution power system outage diagnosis based on root cause analysis(Invited Paper)

Pages

  3672-3680

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.

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  • Cite

    APA: Copy

    Bashkari, M.S., SAMI, A., RASTEGAR, M., & Bordbari, M.J.. (2019). Distribution power system outage diagnosis based on root cause analysis(Invited Paper). SCIENTIA IRANICA, 26(6 (Special Issue on: Transactions D: Computer Science & Engineering and Electrical Engineering)), 3672-3680. SID. https://sid.ir/paper/290880/en

    Vancouver: Copy

    Bashkari M.S., SAMI A., RASTEGAR M., Bordbari M.J.. Distribution power system outage diagnosis based on root cause analysis(Invited Paper). SCIENTIA IRANICA[Internet]. 2019;26(6 (Special Issue on: Transactions D: Computer Science & Engineering and Electrical Engineering)):3672-3680. Available from: https://sid.ir/paper/290880/en

    IEEE: Copy

    M.S. Bashkari, A. SAMI, M. RASTEGAR, and M.J. Bordbari, “Distribution power system outage diagnosis based on root cause analysis(Invited Paper),” SCIENTIA IRANICA, vol. 26, no. 6 (Special Issue on: Transactions D: Computer Science & Engineering and Electrical Engineering), pp. 3672–3680, 2019, [Online]. Available: https://sid.ir/paper/290880/en

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