Abstract. In this paper, the potential of Dynamic Induction Control (DIC), which has shown promising results in recent simulation studies, is further investigated. When this control strategy is implemented, a turbine varies its induction factor dynamically over time. In this paper, only periodic variation, where the input is a sinusoid, are studied. A proof of concept for this periodic DIC approach will be given by execution of scaled wind tunnel experiments, showing for the first time that this approach can yield power gains in real-world wind farms. Furthermore, the effects on the Damage Equivalent Loads (DEL) of the turbine are evaluated in a simulation environment. These indicate that the increase in DEL on the excited turbine is limited.

Wind condition awareness is an important factor to maximize power extraction, reduce fatigue loading and increase the power quality of wind turbines and wind power plants. This paper presents a new method for wind speed estimation based on blade load measurements. Starting from the definition of a cone coefficient, which captures the collective zeroth-harmonic of the out-of-plane blade bending moment, a rotor-effective wind speed estimator is introduced. The proposed observer exhibits a performance similar to the well known torque balance estimator. However, while the latter only measures the average wind speed over the whole rotor disk, the proposed approach can also be applied locally, resulting in estimates of the wind speed in different regions of the rotor disk. In the present work, the proposed method is used to estimate the average wind speed over four rotor quadrants. The top and bottom quadrants are used for estimating the vertical shear profile, while the two lateral ones for detecting the presence of a wake shed by an upstream wind turbine. The resulting wake detector can find applicability in wind farm control, by indicating on which side of the rotor the upstream wake is impinging. The new approach is demonstrated with the help of field test data, as well as simulations performed with high-fidelity aeroservoelastic models

Abstract. The wind field leaves its fingerprint on the rotor response. This fact can be exploited by using the rotor as a sensor: by looking at the rotor response, in the present case in terms of blade loads, one may infer the wind characteristics. This paper describes a wind state observer that estimates four wind parameters, namely the vertical and horizontal shears and the yaw and upflow misalignment angles, from out-of-plane and in-plane blade bending moments. The resulting observer provides on-rotor wind inflow characteristics that can be exploited for wind turbine and wind farm control. The proposed formulation is evaluated through extensive numerical simulations in turbulent and nonturbulent wind conditions using a high-fidelity aeroservoelastic model of a multi-MW wind turbine.

In this work, a new method is proposed for the stability analysis of wind turbines. The method uses input–output time histories obtained by conducting virtual excitation experiments with a suitable wind turbine simulation model. Next, a single‐input/single‐output periodic reduced model is identified from the recorded response and used for a stability analysis conducted according to the Floquet theory. Since only input–output sequences are used, the approach is model independent in the sense that it is applicable to wind turbine simulation models of arbitrary complexity. The use of the Floquet theory reveals a much richer picture than the one obtained by widespread classical approaches based on the use of the multi‐blade coordinate transformation of Coleman. In fact, it is shown here that, for each principal mode computed by the classical approach, there are in reality infinite super‐harmonics of varying strength fanning out from the principal one at multiples of the rotor speed. The relative strength of each harmonic in a fan provides for a way of measuring how periodically one specific fan of modes behaves. The notion of super‐harmonics allows one to justify the presence of peaks in the response spectra, peaks that cannot be explained by the classical time‐invariant analysis. The Campbell diagram, i.e., the plot of system frequencies vs. rotor speed, is in this work enriched by the presence of the super‐harmonics, revealing a much more complex pattern of possible resonant conditions with the per‐rev excitations than normally assumed. Copyright © 2014 John Wiley & Sons, Ltd.

Abstract. As wind turbines in a wind farm interact with each other, a control problem arises that has been extensively studied in the literature: how can we optimize the power production of a wind farm as a whole? A traditional approach to this problem is called induction control, in which the power capture of an upstream turbine is lowered for the benefit of downstream machines. In recent simulation studies, an alternative approach, where the induction factor is varied over time, has shown promising results. In this paper, the potential of this dynamic induction control (DIC) approach is further investigated. Only periodic variations, where the input is a sinusoid, are studied. A proof of concept for this periodic DIC approach will be given by the execution of scaled wind tunnel experiments, showing for the first time that this approach can yield power gains in real-world wind farms. Furthermore, the effects on the damage equivalent loads (DEL) of the turbine are evaluated in a simulation environment. These indicate that the increase in DEL on the excited turbine is limited.