Bond graph modeling and simulation of wind turbine systems

This paper addresses the problem of bond graph methodology as a graphical approach for the modeling of wind turbine generating systems. The purpose of this paper is to show some of the benefits the bond graph approach has, in contributing a model for wind turbine systems. We will present a nonlinear model of a wind turbine generating system, containing blade pitch, drive train, tower motion and generator. All which will be modeled by means of bond graph. We will especially focus on the drive train, and show the difference between modeling with a classical mechanical method and by using bond graph. The model consists of realistic parameters, but we are not trying to validate a specific wind turbine generating system. Simulations are carried out in the bond graph simulation software 20-sim

Multiobjective optimization and multivariable control of offshore wind turbine system

Renewable energy is a hot topic all over the world. Nowadays, there are several sustainable renewable power solutions out there; hydro, wind, solar, wave and biomass to name a few. Most countries have a tendency to want to become greener. According to the European Wind Energy Association (EWEA), the world wide capacity increased with 44.601 [MW] in 2012. From this number, 27 % accounts for new installed wind power, which is the second biggest contributor after solar (37 %). In the past, all new wind parks were installed onshore. During the last decade more and more wind parks were installed offshore, in shallow water (less than 30 [m]). Now, some of the issues related to onshore turbines can be avoided, such as the visual impact, noise and shadow flicker. If one is to speculate about what the future may hold, it is evident that the next step for companies is to install floating wind parks in deeper water (more than 30 [m]). Offshore conditions far from the shore provide with higher and more stable wind conditions. In such deep water, it is no longer economically viable to install bottom-fixed turbines. A solution is to use floating turbine. A floating turbine gives new and interesting challenges to the control community. This dissertation mainly deals with pitch control of a floating wind turbine. The modeling is also to some extend dealt with, e.g. it is the main topic of paper A. Paper A deals with the bond graph methodology as a graphical approach to model wind turbines. This is an alternative to the more classical Newtonian approach. The purpose is not to validate a specific wind turbine system, but rather explore how the bond graph can contribute with a model and give a better understanding ..

Theoretical and experimental study of friction emulation and compensation

Masteroppgave i mekatronikk 2010 – Universitetet i Agder, GrimstadThis project deals with hydraulics, mechanics, electronics, dynamic modeling and control theory. The focus is on constructing a test rigg in order to to emulate desired friction and compensate for this with a control loop. The rigg is modeled in matlab/simulink and at last compared to the physical rigg. The rigg reads sensor values and control the servo valves via a CompactRIO. The controllers that are made and implemented in the matlab/simulink model are PI and LQR tracking with integral action

Robust H∞ dynamic output feedback control synthesis with pole placement constraints for offshore wind turbine systems

The problem of robust ∞ dynamic output feedback control design with pole placement constraints is studied for a linear parameter-varying model of a floating wind turbine. A nonlinear model is obtained and linearized using the FAST software developed for wind turbines. The main contributions of this paper are threefold. Firstly, a family of linear models are represented based on an affine parameter-varying model structure for a wind turbine system. Secondly, the bounded parameter-varying parameters are removed using upper bounded inequalities in the control design process. Thirdly, the control problem is formulated in terms of linear matrix inequalities (LMIs). The simulation results show a comparison between controller design based on a constant linear model and a controller design for the linear parameter-varying model. The results show the effectiveness of our proposed design technique

Wind turbine modeling using the bond graph

This paper addresses the problem of bond graph methodology as a graphical approach for modeling wind turbine systems. In this case, we consider the modeling of a wind turbine system with individual pitch control scheme and the interaction with tower motions. Two different bond graph models are presented, one complex and one simplified. Furthermore, the purpose of this paper is not to validate a specific wind turbine model, but rather show the difference between modeling with a classical mechanical method and by using the bond graph approach. Simulation results illustrate the simplified system response obtained using implementation of the governing equations in MATLAB/Simulink and is compared with a bond graph implementation in the simulation program 20-sim

Linear parameter-varying modelling and control of an offshore wind turbine with constrained information

This study deals with linear parameter-varying modelling and output-feedback H8 control design for an offshore wind turbine. The controller is designed with consideration that not all the information in the feedback loop will be used. This constraint is incorporated into the design procedure. Constrained information means that a special zero-non-zero pattern is forced upon the gain matrix. The constrained controller is obtained based on parameter-dependent Lyapunov functions and formulated in terms of linear-matrix inequalities. Since the functions are dependent on the wind speed and accurate wind speed measurements are rarely available in practice, an extended Kalman filter is used to estimate the wind speed. The controller is designed in such a way that it should maintain its stability and performance even if one of the sensors in the feedback loop should malfunction. The control objectives are to mitigate oscillations in the structure and drivetrain, to smoothen power/torque output in addition to keep the closed-loop system stable. This should be achieved by means of individual blade pitch. A traditional procedure for designing a controller for such a system is to choose an operating point and assume it works in a suitable way under the influence of turbulent wind. In this study, the wind turbine model is obtained from the software fatigue, aerodynamic, structural and turbulence (FAST). To design the controller, the model is linearised about several operating points. The degrees of freedom in the linearised model are chosen according to the controller objectives. The linear models are valid within the span of operating points. Finally, the controller is tested on the fully non-linear system under the influence of turbulent wind and a scenario where one of the sensors in the feedback loop is malfunctioning. The closed-loop response of the presented controller is compared to the closed-loop response of the baseline controller included in the FAST package along with a controller designed based on a single linearised model. © The Institution of Engineering and Technology 2013