Torben Knudsen

Estimation of Rotor Effective Wind Speed: A Comparison

Modern wind turbine controllers use wind speed information to improve power production and reduce loads on the turbine components. The turbine top wind speed measurement is unfortunately imprecise and not a good representative of the rotor effective wind speed. Consequently, many different model-based algorithms have been proposed that are able to estimate the wind speed using common turbine measurements. In this paper, we present a concise yet comprehensive analysis and comparison of these techniques, reviewing their advantages and drawbacks. We implement these techniques and compare the results on both aero-servo-elastic turbine simulations and real turbine field experiments in different wind scenarios.

Brief Consistency analysis of subspace identification methods based on a linear regression approach

In the literature results can be found which claim consistency for the subspace method under certain quite weak assumptions. Unfortunately, a new result gives a counter example showing inconsistency under these assumptions and then gives new more strict sufficient assumptions which however does not include important model structures such as, e.g. Box-Jenkins. Based on a simple least-squares approach this paper shows the possible inconsistency under the weak assumptions and develops only slightly stricter assumptions sufficient for consistency and which includes any model structure.

Plug and Play Process Control Applied to a District Heating System

Abstract The general ideas within plug and play process control (P 3 C) are to initialize and reconfigure control systems just by plug and play. In this paper these ideas are applied to a district heating pressure control problem. First of all this serves as a concrete example of P 3 C, secondly some of the first techniques developed in the project to solve the problems in P 3 C are presented. These are in the area of incremental modelling and control and they make it possible to “plug” in a new sensor and actuator and make it “play” automatically.

Data Driven Modelling of the Dynamic Wake Between Two Wind Turbines

Abstract Wind turbines in a wind farm, influence each other through the wind flow. Downwind turbines are in the wake of upwind turbines and the wind speed experienced at downwind turbines is hence a function of the wind speeds at upwind turbines but also the momentum extracted from the wind by the upwind turbine. This paper establishes flow models relating the wind speeds at turbines in a farm. So far, research in this area has been mainly based on first principles static models and the data driven modelling done has not included the loading of the upwind turbine and its impact on the wind speed downwind. This paper is the first where modern commercial mega watt turbines are used for data driven modelling including the upwind turbine loading by changing power reference. Obtaining the necessary data is difficult and data is therefore limited. A simple dynamic extension to the Jensen wake model is tested without much success. The best model turns out to be non linear with upwind turbine loading and wind speed as inputs. Using a transformation of these inputs it is possible to obtain a linear model and use well proven system identification methods. Finally it is shown that including the upwind wind direction to explain the wake improve the prediction performance.

On Using Wind Speed Preview to Reduce Wind Turbine Tower Oscillations

We investigate the potential of using previewed wind speed measurements for damping wind turbine fore-aft tower oscillations. Using recent results on continuous-time H2 preview control, we develop a numerically efficient framework for the feedforward controller synthesis. One of the major benefits of the proposed framework is that it allows us to account for measurement distortion. This results in a controller that is tailored to the quality of the previewed data. A simple yet meaningful parametric model of the measurement distortion is proposed and used to analyze the effects of distortion characteristics on the achievable performance and on the required length of preview. We demonstrate the importance of accounting for the distortion in the controller synthesis and quantify the potential benefits of using previewed information by means of simulations based on real-world turbine data.

A New Method for Estimating ARMAX Models

Abstract If an ARMAX model has zeros in the MA part which are close to the unit circle, then the one step predictor can have large transients. In this case the standard least squares method for estimation of parameters is not suitable. A new method based on backforecasting is therefore developed. A simulation experiment shows that the new method is superior to standard least squares method for a ordinary third order system.

Simple model for describing and estimating wind turbine dynamic inflow

Wind turbines operate with sudden change in pitch angle, rotor or wind speed. In such cases the wake behind the turbine, achieve steady state conditions only after a certain delay. This phenomenon is commonly called dynamic inflow. There are many models for dynamic inflow. The most accurate use a method that can be characterised as the blade element momentum method plus a dynamic equation for the induction factor. This method then needs calculations along the blade for a number of sections including numerical solution of equations. This is numerical demanding. The simplest models amounts to placing a lead-lag filter after rotor torque and thrust calculated from static tables of the power and thrust coefficients. The filter constants will then vary with average wind speed. The filtered versions of torque and thrust are then an approximate modelling of the dynamic inflow. The dynamic inflow model suggested here places itself in between the most complex and the most simple both in accuracy, numerical demands and physical appeal. The suggested models behavior is demonstrated by simulation and the usefulness for extended Kalman filtering is assessed both via simulated data and real full scale turbine data.

Multi-Agent Model for Fatigue Control in Large Offshore Wind Farm

To control wind turbine fatigue and optimize the fatigue distribution for offshore wind farm, a control network model is proposed based on Multi-Agent theory. A typical model of large-scale offshore wind farm is described. Power fatigue of individual wind turbine is defined. In offshore wind farm, a fatigue distribution estimation approach is studied. The Multi-Agent network is modeled based on the current communication network. All wind turbines act as independent agents, and can self-organize into wind power delivery groups adaptively according to the real wind direction. A solution for automatic agent controller synthesis using Uppaal Tiga and Simulink is presented. The fatigue distribution can be optimized to prolong the service time of a wind farm. This approach can also save some of the maintenance cost due to the expensive logistic visit by helicopters. Finally, a typical simulation result illustrates the feasibility of this multi-agent model.

Wave disturbance reduction of a floating wind turbine using a reference model-based predictive control

Floating wind turbines are considered as a new and promising solution for reaching higher wind resources beyond the water depth restriction of monopile wind turbines. But on a floating structure, the wave-induced loads significantly increase the oscillations of the structure. Furthermore, using a controller designed for an onshore wind turbine yields instability in the fore-aft rotation. In this paper, we propose a general framework, where a reference model models the desired closed-loop behavior of the system. Model predictive control combined with a state estimator finds the optimal rotor blade pitch such that the state trajectories of the controlled system tracks the reference trajectories. The framework is demonstrated with a reference model of the desired closed-loop system undisturbed by the incident waves. This allows the wave-induced motion of the platform to be damped significantly compared to a baseline floating wind turbine controller at the cost of more pitch action.

Optimal control of a ballast-stabilized floating wind turbine

Offshore wind energy capitalizes on the higher and less turbulent wind speeds at sea. The use of floating structures for deeper waters is being explored. The control objective is a tradeoff between power capture and fatigue, especially that produced by the oscillations caused by the reduced structural stiffness of a floating installation in combination with a coupling between the fore-aft motion of the tower and the blade pitch. To address this problem, the present paper models a ballast-stabilized floating wind turbine, and suggests a linear quadratic regulator (LQR) in combination with a wind estimator and a state observer. The results are simulated using aero elastic code and analysed in terms of damage equivalent loads. When compared to a baseline controller, this controller clearly demonstrates better generator speed and power tracking while reducing fatigue loads.