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Decision Tree-Based Preventive Control Applications to Enhance Fault Ride Through Capability of Doubly-Fed Induction Generator in Power Systems

Author

Listed:
  • Dione Vieira

    (Institute of Technology, Graduate Program in Electrical Engineering, Federal University of Para, Belém-PA 66075-110, Brazil)

  • Marcus Nunes

    (Institute of Technology, Graduate Program in Electrical Engineering, Federal University of Para, Belém-PA 66075-110, Brazil)

  • Ubiratan Bezerra

    (Institute of Technology, Graduate Program in Electrical Engineering, Federal University of Para, Belém-PA 66075-110, Brazil)

Abstract

The development of a preventive control methodology to increase the capacity of voltage sag recovery (Fault Ride Through Capability (FRTC)) of a doubly-fed induction generator (DFIG) connected in an electrical network is presented. This methodology, which is based on the decision trees (DT) technique, assists with monitoring and support for security and preventive control, ensuring that wind systems remain connected to the power system even after the occurrence of disturbances in the electric system. Based on offline studies, DT discovers inherent attributes of the FRTC scenario related to electrical system behavior and provides a quick prediction model for real-time applications. From the obtained results, it is possible to check that the DFIG is contributing to a system’s operation security from the availability of power dispatch and participation in the voltage control. It is also noted that the use of DT, in addition to classifying the system’s operational state with good accuracy, also significantly facilitates the operator´s task, by directing him to monitor the most critical variables of the monitored operation state for a given system’s topological configuration.

Suggested Citation

  • Dione Vieira & Marcus Nunes & Ubiratan Bezerra, 2018. "Decision Tree-Based Preventive Control Applications to Enhance Fault Ride Through Capability of Doubly-Fed Induction Generator in Power Systems," Energies, MDPI, vol. 11(7), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1760-:d:156187
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    Cited by:

    1. Anastasios Dounis, 2019. "Special Issue “Intelligent Control in Energy Systems”," Energies, MDPI, vol. 12(15), pages 1-9, August.

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