• DocumentCode
    110844
  • Title

    An Interval NLPV Parity Equations Approach for Fault Detection and Isolation of a Wind Farm

  • Author

    Blesa, Joaquim ; Jimenez, Pedro ; Rotondo, Damiano ; Nejjari, Fatiha ; Puig, Vicenc

  • Author_Institution
    Res. Center for Supervision, Univ. Politec. de Catalunya (UPC), Terrassa, Spain
  • Volume
    62
  • Issue
    6
  • fYear
    2015
  • fDate
    Jun-15
  • Firstpage
    3794
  • Lastpage
    3805
  • Abstract
    In this paper, the problem of fault diagnosis of a wind farm is addressed using interval nonlinear parameter-varying (NLPV) parity equations. Fault detection is based on the use of parity equations assuming unknown but bounded description of the noise and modeling errors. The fault detection test is based on checking the consistency between the measurements and the model, by finding if the formers are inside the interval prediction bounds. The fault isolation algorithm is based on analyzing the observed fault signatures online and matching them with the theoretical ones obtained using structural analysis. Finally, the proposed approach is tested using the wind farm benchmark proposed in the context of the wind farm fault-detection-and-isolation/fault-tolerant-control competition.
  • Keywords
    error analysis; fault diagnosis; fault tolerant control; linear parameter varying systems; wind power plants; fault detection test; fault diagnosis and isolation; fault signatures online observation; fault tolerant control; interval NLPV parity equation approach; interval nonlinear parameter-varying parity equations; interval prediction bounds; modeling errors; noise errors; structural analysis; wind farms; Benchmark testing; Equations; Fault detection; Mathematical model; Uncertainty; Wind farms; Wind turbines; Fault diagnosis; Interval NLPV parity equations; Wind farm; interval nonlinear parameter-varying (NLPV) parity equations; wind farm;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2014.2386293
  • Filename
    6998858