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Extended Isolation Forests for Fault Detection in Small Hydroelectric Plants

Author

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  • Rodrigo Barbosa de Santis

    (Graduate Program in Industrial Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte 31270-901, MG, Brazil)

  • Marcelo Azevedo Costa

    (Graduate Program in Industrial Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte 31270-901, MG, Brazil
    Department of Industrial Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, Belo Horizonte 31270-901, MG, Brazil)

Abstract

Maintenance in small hydroelectric plants is fundamental for guaranteeing the expansion of clean energy sources and supplying the energy estimated to be necessary for the coming years. Most fault diagnosis models for hydroelectric generating units, proposed so far, are based on the distance between the normal operating profile and newly observed values. The extended isolation forest model is a model, based on binary trees, that has been gaining prominence in anomaly detection applications. However, no study so far has reported the application of the algorithm in the context of hydroelectric power generation. We compared this model with the PCA and KICA-PCA models, using one-year operating data in a small hydroelectric plant with time-series anomaly detection metrics. The algorithm showed satisfactory results with less variance than the others; therefore, it is a suitable candidate for online fault detection applications in the sector.

Suggested Citation

  • Rodrigo Barbosa de Santis & Marcelo Azevedo Costa, 2020. "Extended Isolation Forests for Fault Detection in Small Hydroelectric Plants," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6421-:d:396816
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    References listed on IDEAS

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    1. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    2. Ferreira, Jacson Hudson Inácio & Camacho, José Roberto & Malagoli, Juliana Almansa & Júnior, Sebastião Camargo Guimarães, 2016. "Assessment of the potential of small hydropower development in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 380-387.
    3. Kaldellis, J. K. & Vlachou, D. S. & Korbakis, G., 2005. "Techno-economic evaluation of small hydro power plants in Greece: a complete sensitivity analysis," Energy Policy, Elsevier, vol. 33(15), pages 1969-1985, October.
    4. Dursun, Bahtiyar & Gokcol, Cihan, 2011. "The role of hydroelectric power and contribution of small hydropower plants for sustainable development in Turkey," Renewable Energy, Elsevier, vol. 36(4), pages 1227-1235.
    5. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    6. Alexandros Bousdekis & Babis Magoutas & Dimitris Apostolou & Gregoris Mentzas, 2018. "Review, analysis and synthesis of prognostic-based decision support methods for condition based maintenance," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1303-1316, August.
    7. Camila Paes Salomon & Claudio Ferreira & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda de Oliveira & Bruno Silva Torres, 2019. "A Study of Fault Diagnosis Based on Electrical Signature Analysis for Synchronous Generators Predictive Maintenance in Bulk Electric Systems," Energies, MDPI, vol. 12(8), pages 1-16, April.
    8. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
    9. Ohunakin, Olayinka S. & Ojolo, Sunday J. & Ajayi, Oluseyi O., 2011. "Small hydropower (SHP) development in Nigeria: An assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 2006-2013, May.
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