Wind Turbine Control and Monitoring

This chapter presents a control scheme of a variable-speed wind turbine with a permanent-magnet synchronous-generator (PMSG) and full-scale back-to-back voltage source converter. A comprehensive dynamical model of the PMSG wind turbine and its control scheme is presented. The control scheme comprises both the wind-turbine control itself and the power-converter control. In addition, since the PMSG wind turbine is able to support actively the grid due to its capability to control independently active and reactive power production to the imposed set-values with taking into account its operating state and limits, this chapter presents the supervisory reactive-power control scheme in order to regulate/contribute the voltage at a remote location. The ability of the control scheme is assessed and discussed by means of simulations, based on a candidate site of the offshore wind farm in Jeju, Korea.

Actually, variable speed wind turbines are continuously increasing their market share, since it is possible to track the changes in wind speed by adapting shaft speed, and thus maintaining optimal power generation. The more variable speed wind turbines are investigated, the more it becomes obvious that their behavior is significantly affected by the used control strategy. Typically, they use aerodynamic controls in combination with power electronics to regulate torque, speed, and power. The aerodynamic control systems, usually variable-pitch blades or trailing-edge devices, are expensive and complex, especially for larger turbines. This situation provides a motivation to consider alternative control approaches. This chapter deals, therefore, with high-order sliding mode control of doubly-fed induction generator-based wind turbines. This kind of control strategy presents attractive features such as chattering-free behavior (no extra mechanical stress), finite reaching time, and robustness with respect to external disturbances (grid faults) and unmodeled dynamics (generator and turbine). High-sliding mode control appropriateness will be highlighted in terms of sensorless control and enhanced fault-ride through capabilities. Simulations using the NREL FAST code will be shown for validation purposes.

This chapter studies the control problems in grid integration of wind energy conversion systems. Sliding-mode control technique will be used to optimize the control of wind energy conversion systems. The maximum power point tracking control algorithms for variable-speed wind energy conversion systems are presented. The grid integration of wind energy conversion systems can be optimized in terms of power delivered to the grid and providing the voltage support ancillary service at the point of common coupling. The control objective for the grid integration of wind energy conversion systems is to keep the DC-link voltage in a desirable value and the input or output power factors staying unitary. The high-order terminal sliding-mode voltage and current regulators are designed, respectively, to control the DC-link voltage and the current rapidly and exactly. The numerical simulations will be carried out to evaluate the control schemes.

Two different operating modes can be clearly identified in wind turbine control systems. In low wind speeds, the main control objective is the energy capture maximization, whereas in high wind speeds it is desired to regulate turbine power and speed at their rated values. The fulfillment of these different control objectives implies the transition through low controllability operating conditions that impose severe constraints on the achievable performance. The control task is usually tackled using two separate controllers, one for each operating mode, and a switching logic. Although satisfactory control solutions have been developed for low and high wind speeds, controller design needs refinement in order to improve performance in the transition zone. This chapter overviews a control scheme covering the entire operating range with focus on the transition zone. H _∞ and advanced anti-windup techniques are exploited to design a high performance control solution for both operating modes with optimum performance in the transition zone.

This chapter proposes a methodology to design robust control strategies for wind turbines. The designed controllers are robust, multivariable and multi-objective to guarantee the required levels of stability and performance considering the coupling of the wind turbine. The proposed robust controllers generate collective pitch angle, individual pitch angle and generator torque control signals to regulate the electrical power production in the above rated power production zone and to mitigate the loads in the components of the wind turbines, like the drive train, tower, hub or blades, to increase their lifetime. The synthesis of these controllers is based on the H _∞ norm reduction and gain scheduling control techniques via Linear Matrix Inequalities. A wind turbine non-linear model has been developed in the GH Bladed software package and it is based on a 5 MW wind turbine defined in the Upwind European project. The family of linear models extracted from the linearization process of the non-linear model is used to design the proposed robust controllers. The designed controllers have been validated in GH Bladed and an exhaustive analysis has been carried out to calculate fatigue load reduction on wind turbine components, as well as to analyze load mitigation in some extreme cases.

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. 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. This chapter investigates a comparative study on the modeling, analysis, and control synthesis for the offshore wind turbine systems. More specifically, an \( {\mathcal{H}}_{\infty } \) static output-feedback control design with constrained information is designed. Constrained information indicates that a remarkable performance can be achieved by considering less information in the control loop or in the case of sensor failures in practice. Therefore, a special structure is imposed on the static output-feedback gain matrix in the contest of constrained information. A practical use of such an approach is to design a decentralized controller for a wind turbine. This will also benefit the controller in such a way that it is more tolerant to sensor failure. Furthermore, the model under consideration is obtained by using the wind turbine simulation software FAST. Using Linear Matrix Inequality \( ({\mathcal{L}\mathcal{M}\mathcal{I}}) \) method, some sufficient conditions to design an \( {\mathcal{H}}_{\infty } \) controller are provided. Finally, a comprehensive simulation study will be carried out to illustrate the effectiveness of the proposed methodology for different cases of the control gain structures.

The main challenges for the deployment of wind turbine systems are to maximise the amount of good quality electrical power extracted from wind energy. This must be ensured over a significantly wide range of weather conditions simultaneously with minimising both manufacturing and maintenance costs. In consequence to this, the fault tolerant control (FTC) and fault detection and diagnosis (FDD) research have witnessed a steady increase in interest in this application area as an approach to maintain system sustainability with more focus on offshore wind turbines (OWTs) projects. This chapter focuses on investigations of different aspects of operation and control of wind turbine systems and the proposal of a new FTC approach to sustainable OWTs. A typical non-linear state space model of a wind turbine system is described and a Takagi-Sugeno (T-S) fuzzy model of this system is also presented. A new approach to active sensor fault tolerant tracking control (FTTC) for OWT described via T-S multiple models. The FTTC strategy is designed in such way that aims to maintaining nominal wind turbine controller without change in both fault and fault-free cases. This is achieved by inserting T-S proportional state estimators augmented with multiple-integral feedback (PMI) fault estimators to be capable to estimate different generator and rotor speed sensors fault for compensation purposes. The material in this chapter is presented using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic.

Ice accumulation on wind turbines operating in cold regions reduces power generation by degrading aerodynamic efficiency and causes mass imbalance and fatigue loads on the blades. Due to blade rotation and variation of the pitch angle, different locations on the blade experience large variation of Reynolds number, Nusselt number, heat loss, and nonuniform ice distribution. Hence, applying different amounts of heat flux in different blade locations can provide more effective de-icing for the same total power consumption. This large variation of required heat flux highly motivates using distributed resistive heating with the capability of locally adjusting thermal power as a function of location on the blade. Under medium/severe icing conditions, active de-icing with accurate direct ice detection is more energy efficient and effective in keeping the blade ice-free. This chapter includes: (1) A literature study on different methods of ice detection and a review on passive and active anti/de-icing techniques on wind turbines, (2) Development of an optical ice sensing method for direct detection of ice on the blade, including experimental results, (3) Development of an aero/thermodynamic model, which predicts how much heat flux is needed locally for de-icing under variable atmospheric conditions, (4) Experimental results showing a proof of concept of closed-loop de-icing using distributed optical ice sensing and resistive heating, and (5) Numerical modeling of ice melting on a blade for different distributed heater layouts and geometries in order to optimize thermal actuation strategy, improve de-icing efficiency, and reduce power consumption. We conclude with discussions of future directions on distributed ice sensing and thermal actuation for the next generation of de-icing systems on wind turbines.

Wind turbine blades usually achieve a very long operating life of 20–30 years. During their operation, the blades encounter complex loading with a high number of cycles as well as severe weather. All of these factors result in accumulated damage, acceleration of fatigue damage, and even sudden blade failure, which can cause catastrophic damage to the wind turbine. In recent years, many structural health monitoring (SHM) techniques, including global and local methods, have been developed and applied as important and valid tools to detect the damage of wind turbine blades. This chapter provides a comprehensive review and analysis on the state of the art of SHM for blades. Then, the SHM techniques are described in detail. For the global method, this chapter discusses mainly the vibration-based damage detection problem for wind turbine blades given the rotation effects. For the local methods, a fatigue damage detection system used for wind turbine blade is developed using high spatial resolution differential pulse-width pair Brillouin optical time-domain analysis (DPP-BOTDA) sensing system and PZT sensors is introduced to detect the tiny damage under static loading.

This chapter addresses the early detection and isolation of sensor faults in a systematic and unified way and illustrates the approach on wind turbine simulation data. Three problems are successively considered: individual signal monitoring, fault detection and isolation (FDI) in redundant sensors, and FDI based on analytical redundancy. In all three cases, a specific approach to generate fault indicators, also called residuals, is presented and combined with an online statistical change detection/isolation algorithm. The considered case studies consist of wind turbine generator speed monitoring, as well as FDI in the stator current and voltages of a wind-driven doubly fed induction generator. For the latter problem, the fact that the three-phase signals are balanced allows one to determine a simple signal model from which a multiobserver scheme is designed for residual generation.

High performance and reliability are required for floating wind turbines due to the fact that they operate under hard conditions with minimum access for maintenance and high cost of repair. Therefore, the assessment of the severity of possible faults on the floating turbine structure will provide good guidelines once they occur either to employ the appropriate protective strategies such as turbine shutdown, or to continue power operation at reduced or full capacity. Furthermore, it will motivate the development of fault-oriented identification algorithms and fault-tolerant control systems that enhance the floating turbine reliability. As the pitch system has the highest failure rate, the faults of such system are of great interest. Several pitch system faults are considered and compared in this chapter including blade pitch sensor bias and gain faults, in addition to the performance degradation of the pitching mechanism, actuator stuck, and actuator runaway. Regardless of the origin of the fault inside the pitch system, these faults lead to an increased rotor imbalance which has different effects on the turbine structure and the platform motion. A utility-scale turbine mounted on the barge platform concept, and modeled using an aero-hydro-servo-elastic simulation tool is used to simulate these faults, and to study their effects as function of the fault magnitude and the mean wind speed in the full load region.

Because of its minor environmental impact, electricity generation using wind power is getting remarkable. The further growth of the wind industry depends on technological solutions to the challenges in production and construction of the turbines. Wind turbine tower vibrations, which limit power generation efficiency and cause fatigue problems with high maintenance costs, count as one of the main structural difficulties in the wind energy sector. To mitigate tower vibrations auxiliary measures are necessary. The effectiveness of tuned mass damper is verified by means of a numeric study on a 5 MW onshore reference wind turbine. Hereby, also seismic-induced vibrations and soil–structure interaction are considered. Acquired results show that tuned mass damper can effectively reduce resonant tower vibrations and improve the fatigue life of wind turbines. This chapter is also concerned with tuned liquid column damper and a semiactive application of it. Due to its geometric versatility and low prime costs, tuned liquid column dampers are a good alternative to other damping measures, in particular for slender structures like wind turbines.

A semi-active (SA) control system based on the use of smart magnetorheological (MR) dampers to control the structural response of a wind turbine is proposed herein. The innovative approach is based on the implementation and use of a variable-properties base restraint. This is able to modify in real time its mechanical properties according to the instantaneous decision of a given control logic, the latter addressed to control one or more structural response parameters. The smart base restraint is thought to be a combination of a smooth hinge, elastic springs, large-scale adjustable MR dampers, and a control algorithm that instantaneously commands the latter during the motion, making them to modulate the reactive force as needed to achieve the performance goals. The design and operation of such a system are shown with reference to a case study consisting of an almost 100 m tall wind turbine, realized in a 1/20 scale model at the Denmark Technical University (DTU). Shaking table tests have been performed under the action of two different types of wind loads and by using two purposely written control logics, highlighting the high effectiveness of the proposed SA control technique and encouraging to further investigate in such direction.

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 chapter illustrates how to set up an inexpensive but effective Hardware-in-the-Loop (HIL) platform for the test of wind turbine (WT) controllers. The dynamics of the WT are simulated on the open-source National Renewable Energy Laboratory WT simulator called FAST (Fatigue, Aerodynamics, Structures, and Turbulence), which emulates all required input signals of the controller and reacts to the controller commands (almost) like an onshore real turbine of 5 MW. The dynamic torque control system runs on an open hardware Arduino microcontroller board, which is connected to the virtual WT via USB. In particular, the power generation control in the full load region for variable-speed variable-pitch wind turbines is considered through torque and pitch control. The HIL proposed platform is used to characterize the behavior of the WT in normal operation as well as in fault operation. In particular, a stuck/unstuck fault is modeled and the behavior of a proposed chattering torque controller is analyzed in comparison to a baseline torque controller.