Load Reducing Control for Wind Turbines: Load Estimation and Higher Level Controller Tuning based on Disturbance Spectra and Linear Models

The aim of this work is to demonstrate an efficient and pragmatic approach for design and optimization of load reducing controllers for wind turbines. Load reducing control means that, besides the classical rotor speed control loop, load or oscillation signals are included as additional input signals into the controller. Thereby, a multiple-input-multiple-output (MIMO) control design problem arises. While the basic concepts of load reducing control and the achievable load reductions are essentially known from literature and will be summarized, in this work, additional focus is put on the achievable cost reductions. The rating of tower and rotor blades and the different strategies for reducing the Levelized Cost of Energy (LCOE) are discussed. It is motivated that control strategies, aiming at increasing the annual energy production or extending the operational lifetime of the turbine, may be more effective than such reducing the cost of structural components. Special attention is given to the effects of load reducing pitch control on the rating of the pitch actuation system. Detailed methods for evaluating the pitch system loading for small cyclic movements are presented and compared to standard approaches. The design of load reducing pitch controllers is carried out in the frequency domain. This makes sense, because information on the main disturbance, the turbulence of the wind field, can only be given in a statistical sense, in form of frequency spectra. It is shown that common control objectives, as fatigue loads for tower and blades and the maximum expected value of rotor speed deviations, can be evaluated in the frequency domain, based on the power spectral density (PSD) of the considered signals. If the turbine behavior can be approximated by linear models, these PSDs can be calculated very efficiently without the need for comprehensive time domain simulations. For this controller evaluation, np periodic components due to tower shadow and spatially distributed turbulence need to be included in the spectra of the output signals. This is achieved by combining the linear wind turbine models with a CPSD matrix of the output disturbances, derived from measurements or nonlinear simulations of a reference configuration. For the actual control design, different approaches based on H∞ or H2 norm minimization are investigated. These frequency domain approaches are compatible to the controller evaluation based on PSD. It is motivated that the primary use of these multivariable control design approaches is not to find an optimum controller, but to assure the closed loop stability and to handle the couplings between different control loops. By using parametric weighting functions, higher level control design parameters can be introduced, having a more direct relation to performance and robustness properties than parameters of classical controller structures. The actual H∞/H2 controller calculations are thus embedded in a higher level controller tuning scheme, which makes it easier to find the limits of the feasible design region and to decide on a good controller finally. Exemplarily, this hierarchical control design / controller tuning approach is demonstrated for two different types of load reducing pitch controllers: (1) a combined Rotor Speed / Active Tower Damping Controller and (2) an Individual Pitch Controller.