Open Access
An overview of proactive wind turbine control
Author(s) -
Stotsky Alexander,
Egardt Bo,
Carlson Ola
Publication year - 2013
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.5
Subject(s) - drivetrain , turbine , piecewise , wind power , controller (irrigation) , moment of inertia , control theory (sociology) , computer science , pitch control , wind speed , inertia , power (physics) , moment (physics) , torque , engineering , control engineering , automotive engineering , control (management) , mechanical engineering , mathematics , electrical engineering , artificial intelligence , mathematical analysis , agronomy , physics , classical mechanics , quantum mechanics , biology , meteorology , thermodynamics
Abstract Recent achievements in the proactive turbine control, based on the upwind speed measurements, are described in a unified framework (as an extension of the tutorial [1]), that in turn represents a systematic view of the control activity carried out within the Swedish Wind Power Technology Center (SWPTC). A new turbine control problem statement with constraints on blade loads is reviewed. This problem statement allows the design of a new class of simultaneous speed and pitch control strategies based on the preview measurements and look‐ahead calculations. A generation of a piecewise constant desired pitch angle profile which is calculated using the turbine load prediction is reviewed in this article as one of the most promising approaches. This in turn allows the reduction of the pitch actuation and the design of the collective pitch control strategy with the maximum possible actuation rate. Two turbine speed control strategies based on one‐mass and two‐mass models of the drivetrain are also described in this article. The strategies are compared to the existing drivetrain controller. Moreover, postprocessing technique that can be used for estimation of the turbine parameters with improved performance is also discussed. Postprocessing‐based estimation of the turbine inertia moment is given as an example. All the results are illustrated by simulations with a wind speed record from the Hönö turbine, located outside of Gothenburg, Sweden.