Assessing lidar-assisted feedforward and multivariable feedback controls for large floating wind turbines

We assess the performance of two control strategies on the IEA 15 MW reference floating wind turbine through OpenFAST simulations. The multivariable feedback (MVFB) control tuned by the toolbox of the Reference OpenSource Controller (ROSCO) is considered to be a benchmark for comparison. We then tune the feedback gains for the multivariable control, considering two cases: with and without lidar-assisted feedforward control. The tuning process is performed using OpenFAST simulations, considering realistic offshore turbulence spectral parameters. We reveal that optimally tuned controls are robust to changes in turbulence parameters caused by atmospheric stability variations. The two optimally tuned control strategies are then assessed using the design load case 1.2 specified by the IEC 61400 standard. Compared with the baseline multivariable feedback control, the one with optimal tuning significantly reduced the tower damage equivalent load, leading to a lifetime extension of 19.7 years with the assumption that the lifetime fatigue is only caused by the design load case 1.2. With the assistance of feedforward control realized using a typical four-beam lidar, compared with the optimally tuned MVFB control, the lifetime of the tower can be further extended by 4.6 years.</p

Lidars and wind turbine control. Pt. 1

In recent years lidar technology found its way into wind energy. The main application is still the site assessment, but the possibility to optimize the energy production and reduce the loads by nacelle or spinner based lidar systems is becoming an important issue. In terms of control the inflowing wind field is the main disturbance to the wind turbine and most of the wind turbine control is designed to deal with variations in this disturbance. From control theory, the control performance can be improved with the knowledge of the disturbance. Due to the measurement principle and the complexity of the wind lidar assisted control is a wide field of research. The main idea is to divide the problem in a measurement and a control problem. The presented work describes first how wind characteristics, such as wind speed, direction and shears, can be reconstructed from the limited provided information (see Section 9.2). Based on the models of the wind turbines (see Section 9.3) it is investigated in Section 9.4, how well the lidar information can be correlated to the turbines reaction. In the next sections, several controllers are presented, see Table 15. All controllers are designed first for the case of perfect measurement and then adjusted for realistic measurements. The most promising approach is the collective pitch feedforward controller using the knowledge of the incoming wind speed providing an additional control update to assist common collective pitch control. Additional load reduction compared to the sophisticated feedback controllers could be archived (Schlipf et al., 2010a). The concept has been successfully tested on two research wind turbines (Schlipf et al., 2012a; Scholbrock et al., 2013). Then a feedforward control strategy to increase the energy production by tracking optimal inflow conditions is presented. The comparison to existing indirect speed control strategies shows a marginal increase in energy output at the expense of raised fluctuations of the generator torque (Schlipf et al., 2011). A Nonlinear Model Predictive Control (NMPC) is also presented, which predicts and optimizes the future behavior of a wind turbine using the wind speed preview adjusting simultaneously the pitch angle and the generator torque. The NMPC achieves further load reductions especially for wind conditions near rated wind speed (Schlipf et al., 2012b). Furthermore, a cyclic pitch feedforward controller using the measured horizontal and vertical shear is introduced to assist common cyclic pitch control for further reduction of blade loads. Simulations results from Dunne et al. (2012) are promising, but they have to be further investigated under more realistic conditions. Finally, the benefit of lidar assisted yaw control is explored. A promising way to obtain a accurate measurement of the wind direction is to measure it over the full rotor plane ahead of the turbine by lidar. The expected increase of the energy output is about one percent of the annual energy production, when using the wind direction signal from the lidar system instead of the sonic anemometer (Schlipf et al., 2011)

Prospects of multivariable feedforward control of wind turbines using lidar

Current advances in lidar-technology provide the possibility of including wind preview information in the control design. Lidar-assisted collective pitch control is a simple, but promising approach to reduce the rotor speed variation and structural loads for full load operation. This work extends this approach to the transition between partial and full load operations. A multivariable controller is presented, which provides a simple update for the generator torque rate and the minimum pitch angle based on a nonlinear system inversion. The feedforward signals of the generator torque rate and the minimum pitch angle can be combined with conventional feedback controllers and the collective pitch feedforward controller for full load operation. This facilitates the modular application on commercial wind turbines. Simulations with a full aero-elastic wind turbine model and a lidar simulator show improved rotor speed regulation and significant reduction of tower loads, while only slightly decreasing power. Further, possibilities to transform the load reduction into energy increase are outlined

Lidar-based wake tracking for closed-loop wind farm control

This work presents two advancements towards closed-loop wake redirection of a wind turbine. First, a model-based wake-tracking approach is presented, which uses a nacelle-based lidar system facing downwind to obtain information about the wake. The method uses a reduced-order wake model to track the wake. The wake tracking is demonstrated with lidar measurement data from an offshore campaign and with simulated lidar data from a simulation with the Simulator fOr Wind Farm Applications (SOWFA). Second, a controller for closed-loop wake steering is presented. It uses the wake-tracking information to set the yaw actuator of the wind turbine to redirect the wake to a desired position. Altogether, the two approaches enable a closed-loop wake redirection

Wind Field Reconstruction from Nacelle-Mounted Lidars Short Range Measurements

Profiling nacelle lidars probe the wind at several heights and several distances upstream of the rotor. The development of such lidar systems is relatively recent, and it is still unclear how to condense the lidar raw measurements into useful wind field characteristics such as speed, direction, vertical and longitudinal gradients (wind shear). In this paper, we demonstrate an innovative method to estimate wind field characteristics using nacelle lidar measurements taken within the induction zone. Model-fitting wind field reconstruction techniques are applied to nacelle lidar measurements taken at multiple distances close to the rotor, where a wind model is combined with a simple induction model. The method allows robust determination of free-stream wind characteristics. The method was applied to experimental data obtained with two different types of nacelle lidar (five-beam Demonstrator and ZephIR Dual Mode). The reconstructed wind speed was within 0.5 % of the wind speed measured with a mast-top-mounted cup anemometer at 2.5 rotor diameters upstream of the turbine. The technique described in this paper overcomes measurement range limitations of the currently available nacelle lidar technology

Prospects of a collective pitch control by means of predictive disturbance compensation assisted by wind speed measurements

A simple but robust and effective method to improve collective pitch control of variable-speed wind turbines given information on future inflow is proposed. The present paper focuses on the design and prospects of a control concept using predictive disturbance compensation. This feed-forward control structure is based on calculation of a future effective wind speed, on static disturbance compensation from steady turbine data and on estimation of the dynamic behavior. The control strategy is evaluated with regards to stability, robustness and performance in frequency and time domain. The required wind field information is currently not available for common control, but can in general be obtained from measurements with remote sensing technologies and wind modeling. Significant reductions of rotor speed variations, mechanical loads and pitch activity at fatigue and extreme operating conditions are demonstrated

Flatness-based feedforward control of wind turbines using Lidar

Current lidar technology is offering a promising opportunity to take a fresh look at wind turbine control. This work evaluates a flatness-based feedforward approach, that allows to calculate the control action based on trajectories of the rotor speed and tower motion using wind measurements. The trajectories are planned online considering actuator constrains to regulate the rotor speed and minimize tower movements. The feedforward signals of the collective pitch and generator torque update can be combined with conventional feedback controllers. This facilitates the application on commercial wind turbines. Simulations using a realistic lidar simulator and a full aero-elastic model show considerable reduction of tower and shaft loads

Adaptive feed forward control for wind turbines

Der Beitrag beschreibt, wie Windmessungen mit LIDAR in einer Vorsteuerung verwendet werden können, um die Drehzahlschwankungen und damit die Belastungen von Windenergieanlagen zu reduzieren. Kernstück dieser Vorsteuerung ist ein Filter, der adaptiv auf die aktuellen Messungen eingestellt werden muss, da sich die Prädiktionszeit und die Korrelation zwischen Vorhersage und Anlagenverhalten kontinuierlich ändern. Die Ergebnisse werden mit Messdaten einer 5MW Anlage validiert.This paper presents how LIDAR measurements can be used in a feed forward control to reduce rotor speed variation and loads on wind turbines. Core of this control strategy is an adaptive filter that takes into account the continuous changes in the prediction time and in the correlation between the turbine reaction and the preview. Results will be validated with measurement data of a 5MW wind turbine

Control design methods for floating wind turbines for optimal disturbance rejection

An analysis of the floating wind turbine as a multi-input-multi-output system investigating the effect of the control inputs on the system outputs is shown. These effects are compared to the ones of the disturbances from wind and waves in order to give insights for the selection of the control layout. The frequencies with the largest impact on the outputs due to the limited effect of the controlled variables are identified. Finally, an optimal controller is designed as a benchmark and compared to a conventional~PI-controller using only the rotor speed as input. Here, the previously found system properties, especially the difficulties to damp responses to wave excitation, are confirmed and verified through a spectral analysis with realistic environmental conditions. This comparison also assesses the quality of the employed simplified linear simulation model compared to the nonlinear model and shows that such an efficient frequency-domain evaluation for control design is feasible