Wind power turbine control


The goal of the previous project project ’Stochastic Model Predictive Control of Wind Turbines’ was to develop a concept ready novel control architecture for a wind turbine control with extended load mitigation capabilities and power output improvement. The goal of this project has been reached with the following results:

  • A new proactive architecture for simultaneous control of the rotor speed and collective blade pitch angle with constraints on blade loads. The constraints on loads are taken into account explicitly at the stage of the
    control design [1].
  • A new backstepping-based control of the drive train with essential flexibility of the driveshaft. The controller damps driveline oscillations and allows smooth tracking of the desired rotor speed to achieve an optimal turbine performance [1].
  • A new composite turbine control architecture that consists of feedforward and feedback parts based on both upwind speed measurements and wind speed measurements at the turbine site. Feedforward part is based on the upwind speed measurements and includes a run-ahead turbine model and estimation of the derivative in preprocessing using spline interpolation method. High performance derivative signal is further used for proactive regulation of the turbine speed and collective pitch control loops [2], [3].
  • A new robust collective pitch control scheme with upwind speed measurements. The robustness is achieved via introduction of the desired piecewise constant pitch angle profile, that allows reduction of the pitch actuation. Moreover, a new optimal blade pitch regulation with the maximum possible actuation rate is proposed. In addition, a new postprocessing technique for high quality estimation of the turbine parameters is also described [4].
  • A new technique for detection of the mass of blade ice in cold climate. The method is based on data-driven algorithms for estimation of the turbine inertia moment [5].
  • A new individual pitch control architecture with preview measurements of the wind speed at different heights for the turbine tilt moment reduction. The approach includes look-ahead calculations of the desired blade loads and pitch angles as well as preprocessing algorithms for calculation of the derivative of the desired pitch angle [6].
A significant cost reduction of the LIDAR systems is expected in the next coming years, which implies a potential availability of the wind speed preview information for the turbine control system. The results of this project show
potential load reduction and turbine power output improvement due to availability of the wind speed preview information. This in turn enables further increase of the size of wind turbines with reduction of the structural costs.
Two journal papers have been published [1], [2]. Two conference papers were presented [3], [4]. Three journal papers [5], [6] and [7] were accepted for publication.



The research is carried out within Swedish Wind Power Technology Center (SWPTC)

Project time: 2012-2013

​​[1] Stotsky A. and Egardt B., Proactive Control of Wind Turbine with Blade Load Constraints, Proc. IMechE Part I: Journal of Sytems and Control Engineering, vol. 226, N 7, August 2012, pp. 985-993.
[2] Stotsky A. and Egardt B., Model Based Control of Wind Turbines: Look-Ahead Approach, Proc. IMechE Part I: Journal of Sytems and Control Engineering, vol. 226, N 8, September 2012, pp. 1029-1038.
[3] Stotsky A. and Egardt B., Model Based Control of Wind Turbines: Look-Ahead Approach, Proceedings of the 7-th IFAC Symposium on Robust Control Design, The International Federation of Automatic Control, Aalborg, Denmark, June 20-22, 2012, pp. 639-646.
[4] Stotsky A. and Egardt B., Robust Proactive Control ofWind Turbines with Reduced Blade Pitch Actuation, Proc. of the 5-th IFAC Symposium on System Structure and Control, Grenoble, France, February 4-6, 2013.
[5] Stotsky A. and Egardt B., Data-Driven Estimation of the Inertia Moment of Wind Turbines: A New Ice Detection Algorithm, Accepted for publication in Proc. IMechE Part I: Journal of Sytems and Control Engineering.
[6] Stotsky A. and Egardt B., Individual Pitch Control of Wind Turbines: Model-Based Approach, Proc. IMechE Part I: Journal of Sytems and Control Engineering, in print.
[7] Stotsky A., Egardt B. and Carlson O., Control of Wind Turbines: A Tutorial on Proactive Perspectives, submitted to Energy Science & Engineering, 2013.

Published: Fri 06 Oct 2017.