Power generation control of a monopile hydrostatic wind turbine using an H∞ loop-shaping torque controller and an LPV pitch controller

We transform the NREL (National Renewable Energy Laboratory) 5-MW geared equipped monopile wind turbine model into a hydrostatic wind turbine (HWT) by replacing its drivetrain with a hydrostatic transmission drivetrain. Then we design an H∞ loop-shaping torque controller (to regulate the motor displacement) and a linear parameter varying (LPV) blade pitch controller for the HWT. To enhance performances of the pitch control system during the transition region around the rated wind speed, we add an anti-windup (AW) compensator to the LPV controller, which would otherwise have had undesirable system responses due to pitch saturation. The LPV AW pitch controller uses the steady rotor effective wind speed as the scheduling parameter which is estimated by LIDAR (Light Detection and Ranging) preview. The simulations based on the transformed NREL 5-MW HWT model show that our torque controller achieves very good tracking behaviour while our pitch controller (no matter with or without AW) gets much improved overall performances over a gain-scheduled PI pitch controller

Vibration and power regulation control of a floating wind turbine with hydrostatic transmission

We design a blade pitch controller employing linear parameter-varying (LPV) synthesis techniques for a floating hydrostatic wind turbine (HWT) with a barge platform, which is based on the LIDAR (Light Detection and Ranging) preview on the wind speed. The developed control system can simultaneously reduce barge pitch motions and regulate the power in Region 3. These two functions would normally disturb each other if designed separately. The state space model is not affinely dependent on the wind speed thus the LPV controller is obtained by satisfying multiple LMIs evaluated at a set of gridded points within the wind speed range in Region 3. An anti-windup compensation scheme is then used to improve the LPV controller’s performance when the pitch undergoes saturation around the rated wind speed. The simulations based on a high-fidelity barge HWT model show that our pitch controller significantly reduces barge pitch motions, loads on blade bearings & tower, and generator power fluctuations, compared with a gain-scheduled PI pitch controller

Feasibility studies of a converter-free grid-connected offshore hydrostatic wind turbine

Owing to the increasing penetration of renewable power generation, the modern power system faces great challenges in frequency regulations and reduced system inertia. Hence, renewable energy is expected to take over part of the frequency regulation responsibilities from the gas or hydro plants and contribute to the system inertia. In this article, we investigate the feasibility of frequency regulation by the offshore hydrostatic wind turbine (HWT). The simulation model is transformed from NREL (National Renewable Energy Laboratory) 5-MW gearbox-equipped wind turbine model within FAST (fatigue, aerodynamics, structures, and turbulence) code. With proposed coordinated control scheme and the hydrostatic transmission configuration of the HWT, the `continuously variable gearbox ratio' in turbulent wind conditions can be realised to maintain the constant generator speed, so that the HWT can be connected to the grid without power converters in-between. To test the performances of the control scheme, the HWT is connected to a 5-bus grid model and operates with different frequency events. The simulation results indicate that the proposed control scheme is a promising solution for offshore HWT to participated in frequency response in the modern power system

Control of large offshore wind turbines.

Several control strategies are proposed to improve overall performances of conventional (geared equipped) and hydrostatic offshore wind turbines. Firstly, to maximise energy capture of a conventional turbine, an adaptive torque control technique is proposed through simplifying the conventional extremum seeking control algorithm. Simulations are conducted on the popular National Renewable Energy Laboratory (NREL) monopile 5-MW baseline turbine. The results demonstrate that the simplified ESC algorithms are quite effective in maximising power generation. Secondly, a TMD (tuned mass damper) system is configured to mitigate loads on a monopile turbine tower whose vibrations are typically dominated by its first mode. TMD parameters are obtained via H2 optimisation based on a spatially discretised tower-TMD model. The optimal TMDs are assessed through simulations using the NREL monopile 5-MW baseline model and achieve substantial tower load reductions. In some cases it is necessary to damp tower vibrations induced by multiple modes and it is well-known that a single TMD is lack of robustness. Thus a control strategy is developed to suppress wind turbine’s vibrations (due to multiple modes) using multiple groups of TMDs. The simulation studies demonstrate the superiority of the proposed methods over traditional ones. Thirdly, the NREL 5-MW baseline turbine model is transformed into a hydrostatic wind turbine (HWT). An H∞ loop-shaping torque controller and a light detection and ranging-based linear-parameter-varying anti-windup pitch controller are designed for the HWT. The tests on a monopile HWT model indicate good tracking behaviours of the torque controller and much improved performances of the linear-parameter-varying pitch controller over a gain-scheduled PI pitch controller. Finally, the hydraulic reservoir of a barge HWT is made into a bidirectional-tuned- liquid-column-damper (BTLCD) to suppress barge pitch and roll motions. The simulation results validate the effectiveness of the optimal BTLCD reservoir in reducing the tower loads and power fluctuations

Autonomous landing control of highly flexible aircraft based on Lidar preview in the presence of wind turbulence

This paper investigates preview-based autonomous landing control of a highly flexible flying wing model using short range Lidar wind measurements in the presence of wind turbulence. The preview control system is developed based on a reduced-order linear aeroelastic model and employs a two-loop control scheme. The outer loop employs the LADRC (linear active disturbance rejection control) and PI algorithms to track the reference landing trajectory and vertical speed, respectively, and to generate the attitude angle command. This is then used by the inner-loop using H∞ preview control to compute the control inputs to the actuators (control flaps and thrust). A landing trajectory navigation system is designed to generate real-time reference commands for the landing control system. A Lidar (light detection and ranging) simulator is developed to measure the wind disturbances at a distance in front of the aircraft, which are provided to the inner-loop H∞ preview controller as prior knowledge to improve control performance. Simulation results based on the full-order nonlinear flexible aircraft dynamic model show that the preview-based landing control system is able to land the flying wing effectively and safely, showing better control performance than the baseline landing control system (without preview) with respect to landing effectiveness and disturbance rejection. The control system’s robustness to measurement error in the Lidar system is also demonstrated

Power generation control of a hydrostatic wind turbine implemented by model-free adaptive control scheme

The hydrostatic wind turbine (HWT) is a type of wind turbine that uses hydrostatic transmission (HST) drivetrain to replace the traditional gearbox drivetrain. Without the fragile and expensive gearbox and power converters, HWT can potentially reduce the maintenance costs owing to the gearbox and power converter failures in wind power system, especially in offshore cases. We design an MFAC torque controller to regulate the pump torque of the HWT and compared to an H_inf torque controller. Then we design an MFAC pitch controller to stabilise the rotor speed of HWT and compared to a gain-scheduling proportional-integral (PI) controller and a gain-scheduling PI controller with anti-windup (PIAW). The results indicate that MFAC torque controller provides more effective tracking performance than the H_inf controller, and that MFAC pitch controller shows better rotor speed stabilisation performance in comparison with the gain-scheduling PI controller and PIAW

Control of the offshore wind turbine and its grid integration

This thesis investigates the way to reduce the maintenance cost and increase the life cycle of the offshore wind turbines, as in the offshore case maintenance is highly difficult and expensive. Firstly, we study the possibility to replace the vulnerable and expensive DC link capacitor in wind power integration system by the virtual infinite capacitor (VIC), which is a power electronic circuit functioning as a large filtering capacitor. We propose a control algorithm for the VIC. Before applying it to the wind power system, we firstly test it in a simple power factor compensator (PFC) as the output filter capacitor. The simulation results show the effective filtering performance of VIC in low-frequency range. Then, we validate it experimentally by directly injecting the DC voltage together with a 50 Hz ripples to the VIC. The VIC successfully eliminates the ripple and extracts the DC voltage at the output terminals. Besides, the experiment performances are highly consistent with the corresponding simulations, which demonstrates the possibility to use VIC to replace the DC-link capacitor in wind power integration system and use it in other industrial systems. Since the VIC mainly filters the ripple in low frequency range while the DC-link voltage usually includes ripples in two distinct frequency ranges, we further develop it into the parallel virtual infinite capacitor (PVIC), aiming to suppress the voltage ripple in a wider frequency range. The PVIC is applied to replace the DC-link capacitor in wind turbine grid integration system. The simulations are conducted under different grid conditions with turbulent wind input. The results show that the PVIC provides much better voltage suppression performance than the equivalent DC-link capacitor, which facilitates the power generation control under normal operations and reduces the risks of converter failure under grid faults. In this way, the PVIC proves to be a great solution to substitute the vulnerable DC-link voltage in the offshore wind turbine power integration system. The wind power conversion system from the generator to the grid is composed of a DC-link capacitor and two back-to-back power converters. Though the application of PVIC removes the fragile DC-link capacitor in the power conversion system, the power converters are also fragile and expensive. In addition, the existence of power converters decouples the generator with the grid, which hinders the direct inertia support and frequency regulations from wind turbines. It would be desirable to completely remove the whole power conversion system. Hydrostatic wind turbine (HWT) may provide a suitable solution. The HWT is a wind turbine using hydrostatic transmission (HST) to replace the original heavy and fragile gearbox. The HST can provide the ‘continuously variable gearbox ratio’ , which allows HWT to be connected to a synchronous generator (SG) and then directly to the grid. We propose a coordinated control scheme for the HWT. The simulations are conducted with turbulent wind under variable system loads. The results indicate that with the proposed coordinated control system, the HWT (without power converters) provides efficient frequency support to the grid, which shows it is a promising solution for the future offshore wind power system. Finally, we consider to further reduce the maintenance cost and improve the performance of the HWT by using a new and novel control algorithm called model-free adaptive control (MFAC). It is applied to both torque control and pitch control of the HWT. Their control performances are compared to some of the existing algorithms. The simulation results demonstrate that the MFAC controller has much better tracking and disturbance rejection performances than the existing algorithms which can increase the fatigue life of the wind turbine and reduce the maintenance cost

Advanced control for floating offshore wind turbines.

El contenido de los capítulos 3, 4 y 5 está sujeto a confidencialidad. 117 p.os aerogeneradores flotantes presentan diversos retos tecnológicos, entre los cuales, las atenuaciones de la dinámica producida por el empuje del viento y la inducida por el oleaje, debido a la baja rigidez hidrodinámica de la plataforma, son vitales. Estas dinámicas no solo influyen en el funcionamiento normal del aerogenerador, sino que además, incrementan las cargas mecánicas de algunos componentes, como la torre y palas del aerogenerador. Por ello, el objetivo de esta tesis es minimizar las dinámicas de los aerogeneradores flotantes, mejorando el funcionamiento a la vez que se reducen las cargas mecánicas producidas en la torre y palas mediante técnicas de control avanzadas, y así, aumentar la eficiencia del aerogenerador y prolongar la vida útil de dichos componentes.La descripción del trabajo incluye el modelado de plataformas flotantes y el desarrollo de dos lazos de control, que respectivamente realimentan la velocidad de la góndola y los momentos flectores en las raíces de las palas, para la contribución en la regulación del ángulo de pitch de las palas del aerogenerador. Además, se estudia la relación de las dimensiones de las plataformas flotantes y el desempeño del controlador diseñado con el fin de reducir las dimensiones de la plataforma manteniendo las propiedades del funcionamiento del aerogenerador. Se proponen dos métodos innovadores para la linealización de los modelos no lineales de aerogeneradores flotantes y la optimización de los lazos de control diseñados en esta tesis. Los resultados mostrados demuestran la eficacia del controlador diseñado en la consecución de los objetivos propuestos

Advanced control for floating offshore wind turbines.

El contenido de los capítulos 3, 4 y 5 está sujeto a confidencialidad. 117 p.Los aerogeneradores flotantes presentan diversos retos tecnológicos, entre los cuales, las atenuaciones de la dinámica producida por el empuje del viento y la inducida por el oleaje, debido a la baja rigidez hidrodinámica de la plataforma, son vitales. Estas dinámicas no solo influyen en el funcionamiento normal del aerogenerador, sino que además, incrementan las cargas mecánicas de algunos componentes, como la torre y palas del aerogenerador. Por ello, el objetivo de esta tesis es minimizar las dinámicas de los aerogeneradores flotantes, mejorando el funcionamiento a la vez que se reducen las cargas mecánicas producidas en la torre y palas mediante técnicas de control avanzadas, y así, aumentar la eficiencia del aerogenerador y prolongar la vida útil de dichos componentes.La descripción del trabajo incluye el modelado de plataformas flotantes y el desarrollo de dos lazos de control, que respectivamente realimentan la velocidad de la góndola y los momentos flectores en las raíces de las palas, para la contribución en la regulación del ángulo de pitch de las palas del aerogenerador. Además, se estudia la relación de las dimensiones de las plataformas flotantes y el desempeño del controlador diseñado con el fin de reducir las dimensiones de la plataforma manteniendo las propiedades del funcionamiento del aerogenerador. Se proponen dos métodos innovadores para la linealización de los modelos no lineales de aerogeneradores flotantes y la optimización de los lazos de control diseñados en esta tesis. Los resultados mostrados demuestran la eficacia del controlador diseñado en la consecución de los objetivos propuestos

Machine learning based modelling and control of wind turbine structures and wind farm wakes

With the fast development of wind energy, new technological challenges emerge, which calls for new research efforts to further reduce the cost of wind power. A lot of efforts have been spent to tackle the modelling and control of wind turbines and wind farms. However, big research gaps still exist due to the complexity and strong nonlinearity of the underlying structural and fluid systems. On the other hand, machine learning (ML), which is very powerful in handling complex and nonlinear systems, is developing very fast in the past years. Therefore, this thesis aims to tackle the modelling and control issues arising from the fast-developing wind industry, based on both traditional methods (including structural mechanics, control engineering, fluid dynamics, and scientific computing) and ML (including reinforcement learning, supervised ML, dimensionality reduction, generative adversarial network, and physics-informed deep learning). First, at the turbine level, mitigation of dynamic response of a floating wind turbine using active tuned mass dampers is investigated, where a reinforcement learning algorithm is employed and a neural network structure is designed to realize the employed algorithm. Second, at the farm level, novel static and dynamic wind farm wake models are developed by proposing novel ML-based surrogate modelling methods for distributed fluid systems and then training the model based on highfidelity CFD database generated by large eddy simulations. Third, the prediction of the spatiotemporal wind field in the whole domain in front of a wind turbine is investigated by combining data (i.e. LIDAR measurements at sparse locations) and physics (i.e. Navier-Stokes equations) in a unified manner via physics-informed deep learning. The results presented in this thesis fully demonstrate the great performance of the proposed structural controllers, the great accuracy, efficiency & robustness of the developed wind farm models, and the great accuracy of the full spatiotemporal wind field predictions. xi