Disturbance Accommodating Control Design for Wind Turbines Using Solvability Conditions

Irving Paul Girsang Jaspreet Singh Dhupia School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore, 639798 irving1@e.ntu.edu.sg , djaspreet@ntu.edu.sg ABSTRACT Wind turbine s commonly operat e in an uncertain and noisy environment . Disturbance accommodating controller (DAC) has shown promis ing results in dealing with changing wind speed to regulate generator speed at its rated speed in above rated wind speed condition . However, it has been reported that the number of considered system modes (or degrees of freedom) in design of DAC affects th e system performance. Simulation using high order model, higher than that is considered in the control design, showed unstable response due to effect from the unmodeled structural dynamic s. In this study, DAC with Kalman estimator is designed for variable pitch wind turbines to take into account the unmodeled dynamics and noise measurement . The control performance is simulated using high order FAST model that ha s active generator, drive -train, blade, and tower dynamics in Simulink environment. Simulation re sults show that DAC with Kalman estimator gives best performance in terms of speed regulation and control cost, compared to two other linear controllers: Gain Scheduled Proportional Integral (GSPI) controlle r and DAC with linear estimator . INTRODUCTION Var iable speed variable pitch w ind turbine operates in four major operating regions. Region 1 lies below the cut -in wind speed, below which the wind speed is too low for energy production. Region 2 lies between the cut -in wind speed and the rated wind speed. In this region, the turbine operates to capture as much wind energy as possible. Region 3 , which is considered in this paper, lies between the rated wind speed and the cut -out wind speed. In this region, the turbine operates to produce constant power outpu t at its rated power. This constant rated power can be achieved by operating the turbine at constant generator torque and constant generator speed through feedback control and pitchable blades. The last region, Region 4, lies above the cut -out wind speed , above which the turbine is parked to prevent damage on wind turbine structure due to enormous loads coming from the extremely high wind speed . The p redominant methods of regulating constant generator speed in Region 3 are linear control methods utilizing blade pitch actuation. Common controller types are the model -based Proportional ±Integral -Derivative (PID) controller and Disturbance Accommodating Controller (DAC) [1 -6]. DAC using linear estimator approach has been shown to be effective in attenuating win d disturbances that act as the process noise on wind turbine s [3 -7]. However, this approach is sensitive to mode ling error s, as reported by Wright [6] , that DAC simulation with the activated unmodeled turbine ¶VV WUXFWXUDO dynamics, i.e. turbine with higher order dynamics, can le ad to unstable system response . Moreover, when measurement noise is present, which is not considered in the controller design, additional low pass filter is required to prevent noisy control signal , which can cause problems such as c hattering and controller saturation . This paper presents a robust control approach based on disturbance accommodating control concept for variable pitch wind turbines that compensates for both unmodel ed dynamics, i.e. model ing errors, and external disturba nces , i.e. wind speed input and measurement noise. This approach utilizes Kalman estimation in the feedback loop to estimate both system and disturbance states from noisy measurement signal. Comprehensive formulation and analysis of disturbance accommodati ng controllers using Kalman estimat or can be found in [ 8]. S ome practical advantages of implementing the Kalman estimator in DAC include easy tuning of the estimator parameters, i.e. the noise covariance ASME 2012 5th Annual Dynamic Systems and Control Conference joint with theJSME 2012 11th Motion and Vibration ConferenceDSCC2012-MOVIC20121 Copyright © 2012 by ASME

DAC is a linear control technique used to mitigate the effect of disturbance on the plant. It is a superposition of full state feedback and disturbance feedback. This paper presents a control technique based on Disturbance Accommodation Control (DAC) to reduce fatigue on drive train generated by wind which is combination of step and periodic disturbances (generated by wind shear and tower shadow) of the turbine for above rated wind speed (Region III). We have presented a wind modeling for wind shear and tower shadow effect for the wind turbine control simulation and also developed a control scheme to mitigate the effect of 3p flicker on drive train. 5MW wind turbine of the National Renewable Laboratories (NREL) is used as research object and results are simulated in MATLAB/Simulink. We designed the controller based on linearized model of the wind turbine generated for above rated wind speed and then tested its performance on the nonlinear model of wind turbine. We have shown a comparison of the results for proportional-integral(PI) and proposed DAC controller tested on nonlinear model of wind turbine. Result shows that our proposed controller shows better mitigation of flicker generated due to 3p effect by using collective pitch control as compared to PI with tower and actuator dynamics.

Light detection and ranging (LIDAR) systems can be used to provide wind inflow information to a wind turbine controller before the wind reaches the turbine. Both fatigue and extreme load reduction are possible as a result; in this research, we propose a LIDAR‐based controller designed to prevent emergency shutdowns caused by rotor overspeed. This switching controller consists of a disturbance accommodating control (DAC)‐based baseline controller and a different DAC linearized about a reduced generator speed for extreme events, also referred to as an extreme event controller. Switching between the controllers was performed using linear interpolation over various transition times, depending on how early the extreme event could be detected. If a gust of wind is detected using LIDAR measurements evaluated by a one‐sided cumulative summation algorithm, a relatively long transition time can be used. Switching can also be based on a large output estimation error,εy, in which case the transition time is shorter. Once the extreme event passed, control is switched from the extreme event controller back to the baseline DAC. This switching controller resulted in fewer overspeeds when compared with the modified baseline controller, which is a gain scheduled DAC. By preventing overspeeds, the switching controller increased the mean power the wind turbine generated over a simulated 10 min period. Copyright © 2014 John Wiley & Sons, Ltd.

Individual pitch control (IPC) for wind turbine load reduction in Region 3 operation is improved when wake interaction is considered. The Larsen wake model is applied for composing the rotor wind profile for downstream turbines under wake interaction. The wind profile of the turbine wake was generated by modifying the NREL’s TurbSim codes. The state-space models of wind turbine were obtained via linearization of wind turbine model available in the NREL’s aeroelastic design code FAST. In particular, in order to obtain more accurate state-space models, equivalent circular wind profile was generated so as to better determine the local pitch reference. Based on such models, IPC controllers were designed following the disturbance accommodating control (DAC) and periodic control framework. The simulation results showed that the turbine loads can be further reduced using the switching control scheme based on wake modeling, as compared with the generic DAC without wake consideration.

This work presents the results from a field test of LIDAR assisted collective pitch control using a scanning LIDAR device installed on the nacelle of a mid-scale research turbine. A nonlinear feedforward controller is extended by an adaptive filter to remove all uncorrelated frequencies of the wind speed measurement to avoid unnecessary control action. Positive effects on the rotor speed regulation as well as on tower, blade and shaft loads have been observed in the case that the previous measured correlation and timing between the wind preview and the turbine reaction are accomplish. The feedforward controller had negative impact, when the LIDAR measurement was disturbed by obstacles in front of the turbine. This work proves, that LIDAR is valuable tool for wind turbine control not only in simulations but also under real conditions. Furthermore, the paper shows that further understanding of the relationship between the wind measurement and the turbine reaction is crucial to improve LIDAR assisted control of wind turbines.

Kω2 control, also called torque control, is a popular tool for maximizing wind turbine power in region 2. For hydrostatic wind turbines, the Kω2 law relates pressure and rotor speed. This work considers implementing the Kω2 law as pressure-regulation or rotor speed-regulation. Dimensionless, linearized models of these two approaches are used to investigate dynamics and control. Analysis shows that the mechanical rotor dynamics are much slower than the hydraulic transmission dynamics and that frictional and leakage losses have a negligible effect on system dynamics. Root locus analysis shows how systems responses change with variation of PID controller gains. Both control approaches require derivative controller action to sufficiently damp their responses; both are also fundamentally limited in their speed of response by a slow stable pole regardless of their controller loop gains. Nonlinear system simulation shows that both control approaches track the maximum power point with nearly identical transient behavior and experience nearly identical power losses when using suboptimal values of the control law gain K.

This paper presents an initial investigation on improving individual pitch control (IPC) for wind turbine load reduction for Region 3 operation with the wake interaction included under the context of wind farm operation. The Jensen wake model is applied for composing the rotor wind profile for downstream turbines under wake interaction, and switched controllers were thus developed based on the composite wind profile. The wind profile of the turbine wake was generated by modifying the NREL’s TurbSim codes. The state-space models of wind turbine were obtained via linearization of wind turbine model available in the NREL’s FAST. In particular, in order to obtain more accurate state-space models for IPC design, equivalent circular wind profile was generated. Based on such models, IPC controllers were designed following the disturbance accommodating control (DAC) and periodic control framework for load reduction when wake interaction was considered. The simulation results showed that the turbine loads can be further reduced using the switching control scheme based on wake modeling, as compared with the generic DAC without wake consideration.

Aiming at the Megawatt (MW) scale wind turbine, a dynamic analysis and simulation method is presented to research blade loads and dynamic characteristics. To consider blade flexible deformation, the whole blade was divided into a number of units. Each unit was treated as a rigid body, the flexible connection between two adjacent units is considered. A nacelle coordinate system, a rotating shaft coordinate system, and a blade coordinate system were employed to describe the wind turbine blade. In those coordinate systems, blade inertial load calculation model, centrifugal force load calculation model and gravity load calculation model are established. Combining load model with the whole model of wind turbines, the real-time dynamic simulation model of blade loads was established in Simulink circumstance and a numerical simulation was performed. Based on the simulation analysis, some research results were obtained. When the large instantaneous fluctuation of electromagnetic torque of generator happens, rotor speed does not appear to have large fluctuation due to the inertia of the wind rotor, but the blade vibration speed changes obviously. Gravity has a periodic variation in the process of blade rotation and has a large influence on the edgewise moment. The research results provide a helpful reference for the structure design, operation, and control of wind turbines.

This paper proposes a design of sophisticated multi-Objective H 2 /H ∞ collective pitch controllers using linear Matrix Inequalities' techniques. The proposed controller's design takes into account model uncertainties by designing a controller based on a polytopic model. The LMI-based approach allows additional constraints to be included in the design (e.g. H ∞ problem, H 2 problem, H ∞ /H 2 trade-off criteria, and pole clustering).These constraints are exploited to include requirements for perfect regulation, efficient disturbance rejection, and permissible actuator usage. The proposed controller is compared to an optimal linear quadratic regulator pitch controller based on single model. Both controllers are tested on 5-MW Reference wind turbine model developed by NREL using FAST software code.

Wind energy is currently the fastest growing electricity source. To meet the output demand, wind turbines are becoming larger and more flexible leading to the problems of structural load especially in case of offshore turbines. Advanced control algorithms are developed to reduce the load, allowing to build larger turbines, and expand their lifetime. Observer-based control algorithms such as Linear-Quadratic-Gaussian LQG control which uses LQR to calculate the optimal observer and controller gains are commonly applied to wind turbines in literature. However the approach requires to calculate the observer and control gains separately. In addition, linear models used for parameter calculation may have errors with respect to the nonlinearities of wind turbines and induced to unmodeled dynamical properties. These modeling errors need to be considered to to guarantee the stability of the controlled system. Alternatively a robust design assuming bounds and limits of models have to be realized to guarantee stability while ignoring details of modeling. This paper proposes an optimal robust observer-based state feedback controller for large-scale wind turbines to realize multi objectives, including structural load mitigation and rotor speed regulation. The novel contribution is that the observer gain parameters, control gains, and integral action are optimized at the same time within H∞ mixed sensitivity framework to achieve desired performance with respect to power regulation, structural load mitigation, and also robustness for the wind turbine control system. The control performances have been verified by a high fidelity simulation software and are compared to those of a classical baseline controller.

This chapter presents a low-cost, flexible lab test-bench wind farm for advanced research and education on wind turbine and wind farm design and control. The mechanical, electrical, electronic and control system design of the wind turbines, along with the dynamic models, parameters and classical pitch and torque controllers are introduced in detail. Furthermore, the study presents a variety of experiments that (a) quantifies the effect of the number of blades in the aerodynamic efficiency, (b) estimates the generator efficiency, (c) validates the rotor-speed pitch control system, (d) proves the concept of maximum power point tracking for individual wind turbines, (e) estimates the aerodynamic C p /λ characteristics, (f) calculates the power curve, and (g) studies the effect of wind farm topology configurations on the individual and global power efficiency. The experimental results prove that the dynamics of the test-bench corresponds well with full-scale wind turbines. This fact makes the test-bench wind farm appropriate for advanced research and education in wind energy systems.

This work discusses the design of a nonlinear controller for a single mass model of a variable speed wind turbine without measurement of wind speed. Dynamic load on the drive train shaft plays a vital role in turbine lifespan. So the design of the nonlinear controller should pay more care in mitigation of transient load on the drive train shaft. The objective of the controller is to extract the optimal power with limited dynamic loads on the shaft. The above objectives are satisfied by tracking the reference rotor speed which is done by a nonlinear controller. Effective wind speed is obtained by Modified Newton Raphson (MNR), which is used for deriving the reference rotor speed. In this paper, a nonlinear controller, i.e. double integral sliding mode controller (DISMC) is proposed for the single mass model of a wind turbine at partial load region (below rated wind speed). Lyapunov candidate function is used for analyzing the stability of the proposed controller. The performance of the proposed controller is compared with conventional integral sliding mode controller (ISMC) in terms of performance parameters. The robustness of the controllers are analyzed in the presence of different input disturbances and different wind speed profiles. From results, it is found that DISMC can able to accommodate various input disturbance level up to 5kNm.

The demand for electricity is continuously growing around the world and thus the need for renewable and long-lasting sources of energy has become an essential challenge. Wind turbines are considered one of the major sources of renewable electricity generation. Therefore, there is a crucial demand for wind turbine model and control systems that are capable of precisely simulating the actual wind power systems. In this paper, an advanced fuzzy logic controller is proposed to control the speed of a wind turbine system. Initially, aero dynamical, mechanical and electrical models of two mass wind turbines models are derived. Analytical calculation of the power coefficient is adopted through a nonlinear function of six coefficients that mainly depends on pitch angle and tip speed ratio. The ultimate power output from the turbine can reach up to 50 % which is achieved at zero pitch angle with an approximately tip speed ratio of eight. This is then followed by designing a hybrid fuzzy-plus I pitch controller to regulate the speed of the wind turbine shaft. In general, fuzzy logic control strategy have the advantages over traditional control techniques especially when the system is highly non-linear and has to deal with strong disturbances such as wind turbulence. To evaluate the reliability and robustness of the controller, the response of the wind turbine system is tested under several types of disturbances including wind fluctuation, sudden disturbances on high and low speed shafts. Simulation findings reveals that the performance of fuzzy-integral control technique outweighs that of conventional fuzzy approach in terms of multiple performance evaluation indexes such as zero overshoot and steady state error, rise time and a settling time of (32.9 s) (44.7 s) respectively. The reliability and robustness of the controller is tested by applying speed and torque disturbances of 25% of their maximum ranges. Results have revealed that the controller was able to reject all disturbances efficiently with a change in pitch angle up to a maximum of 10 degrees in order to retain a constant rotor speed at 1000 rpm.

The paper discusses some of the recent developments in vibration control strategies for wind turbines, and in this context proposes a new dual control strategy based on the combination and modification of two recently proposed control schemes. Emerging trends in the vibration control of both onshore and offshore wind turbines are presented. Passive, active and semi-active structural vibration control algorithms have been reviewed. Of the existing controllers, two control schemes, active pitch control and active tendon control, have been discussed in detail. The proposed new control scheme is a merger of active tendon control with passive pitch control, and is designed using a Pareto-optimal problem formulation. This combination of controllers is the cornerstone of a dual strategy with the feature of decoupling vibration control from optimal power control as one of its main advantages, in addition to reducing the burden on the pitch demand. This dual control strategy will bring in major benefits to the design of modern wind turbines and is expected to play a significant role in the advancement of offshore wind turbine technologies.

Performance evaluation of full-scale tuned liquid dampers (TLDs) for vibration control of large wind turbines using real-time hybrid testing