Blade Pitch Actuator Research Articles

Impact of Blade Pitch Actuation System on Wind Turbine Cost and Energy Production

To minimize the levelized cost of energy (LCOE) of wind turbines, advanced co-design strategies are required that also consider the contribution of active blade pitch control to overall energy production and wind turbine cost. Thereby, the demanded closed-loop performance drives the requirements on the blade pitch actuation system, which needs to be carefully balanced. To enable this, an extended LCOE measure is developed in this paper using stochastic estimates for quantifying pitch actuation cost in terms of pitch power and closed-loop performance in terms of net energy production. Additionally, the impact of blade pitch deflections on structural loads and hence cost is evaluated considering both collective and individual pitch control. The interdependencies between the different design objectives are revealed in a case study carried out on a 25MW wind turbine, demonstrating the guidance for engineers toward cost-effective and efficient wind turbine designs.

Active alleviation of fatigue stress on blades by adaptively maneuvered deformable trailing edge flaps (DTEF).

The concept of "smart rotor" is an evolving advancement in wind turbine which enables an intelligent active flow control in rotor. The deformable trailing edge flap (DTEF) is a part of smart rotor concept which implements a customized active load control. The trailing edge flap actuator effectively replaces the tedious blade pitch actuation and conserves the actuation energy required for pitching the entire blade. The DTEFs require a fast computing, anticipatory controller for optimally tuning the flap angle with minimal power compromise. This work analyzes the performance of advanced control strategies like model predictive control (MPC), adaptive MRAC control, and DQ controllers. The MRAC controller is found to reduce the fatigue stress by 40% and the MPC controller damps up to 70% more efficiently than the typical feedback controller. The control strategies are aided by the LiDAR-based preview wind data for the active manipulation of trailing edge flap angle control. The validation of proposed controller is done using power analysis curve and the component fatigue lifetime analysis using MLIFE software. The above analyses are done in NREL Onshore 5-MW FAST wind turbine model which could be interfaced with MATLAB with modified AeroDyn code for active flap deflection.

A novel resonant controller for sea-induced rotor blade vibratory loads reduction on floating offshore wind turbines

A novel multi-layer control approach for offshore floating wind turbines is presented, suitable for alleviating the vibratory loads while keeping the generator power output stable. It consists of the simultaneous application of different control strategies, each optimized for a specific objective. The proposed multi-layer scheme’s main scope is to reduce the Levelized Cost of Energy. Two resonant controllers based on collective blade pitch actuation are applied for the rejection of the vibratory loads induced by sea waves. In contrast, a proportional–integral controller, fed by measured cyclic blade root flapping moments, provides the blade cyclic pitch to be actuated to reduce blade root loads at the rotor revolution frequency. The proposed control strategy is validated by simulations on: (i) the NREL (U.S. National Renewable Energy Laboratory) 5 MW wind turbine, supported by a spar buoy or a semi-submersible platform; (ii) the 15 MW IEA (International Energy Agency) wind turbine supported by a semi-submersible platform. These show that significant reductions of the vibratory blade root flapping moments and rotor nacelle assembly loads are achievable, thus demonstrating the good potential performance of the controller introduced.

Multi model robust control design for a floating offshore variable speed wind turbine with tension leg platform

This paper presents a multi-model robust control (MMRC) design for an offshore variable speed wind turbine with tension leg platform. The proposed control scheme covers the model uncertainty in the above rated wind speed, and it provides a reliable control for power regulation while minimizing the mechanical loads on the wind turbine structure. For this purpose, the above rated wind speed region is divided into several wind speed groups, and a set of linearized models are obtained from the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) simulator for various mean wind speeds of each group. Using Weibull wind speed distribution, a nominal model with additive uncertainty is generated for each wind speed group, to be used in the multi-model robust control design. The MATLAB/Simulink software environment is used to verify the performance of the proposed control strategy using the National Research Energy Laboratory (NREL) three-bladed horizontal axis 5-MW baseline wind turbine. The performance of the proposed multi-model robust controller is compared with the state-of-the-art gain-scheduling PI (GSPI) controller. The results show improvement in power regulation and platform movement minimization while reducing the mechanical loads of the wind turbine. By using the proposed control scheme, the severe oscillation in the blade pitch actuation and power output, which is due to the changes in the operating point of the wind turbine, decreases drastically.

Application of artificial intelligent technique to maximize power yielding ability of wind turbine

ABSTRACT This article is about the application of artificial intelligence (AI) to maximize the energy-yielding ability of wind turbines from a renewable energy source. This is done by maximizing the wind turbine power conversion coefficient (Cp) considering the impacts of changes in the wind turbine blade tip speed ratio (λ) and pitch angle (β) according to the fluctuation in wind speed. A fuzzy inference system is used to optimize the Cp in a blend with the blade pitch actuator control. When the wind speed was low, the controller of the pitch actuator reduces β and optimally kept the plane of the blade in the wind flow direction. Also, it optimized the λ of the blade by maintaining the speed of the turbine around a rated value. The simulation result indicated the maximum Cp of 0.5580. This is equivalent to a 7.31% improvement in energy-yielding in comparison to recent most research works. The study is verified using real-time wind data of Adama-Ethiopia, and technical data of the SE7715 wind turbine and its factory test data by employing MATLAB software. Accordingly, a successful improvement in power harvesting capacity is attained, which is in the advance of results in recent literature. Thus, wind energy harvesting can be enhanced by the Cp maximization technique together with a pitch drive system.

Improving Power Harvesting Ability of Variable Speed Wind Turbine using Intelligent Soft Computing Technique

This paper presents a study carried out on maximizing energy harvesting of wind turbines. One way of improving the output power of the wind turbines is by optimizing the power conversion coefficient. The power conversion coefficient factor is expressed as a function of the wind turbine blade tip speed ratio and the turbine blade pitch angle. Optimization of the wind turbine generator output power is done by considering the effects of variations of wind speed, blade tip speed ratio, and pitch angle. An intelligent soft computing technique known as an adaptive neuro-fuzzy inference system (ANFIS) with a fuzzy logic controller for blade pitch actuator was applied to optimize the generator output power. The simulation result showed that the power conversion coefficient of 0.513 is achieved. The study was verified by using real-time wind speed data of Adama II wind farm in Ethiopia and specifications of the Gamesa G80 horizontal axis wind turbine generator unit by MATLAB software. Accordingly, a promising and satisfying improvement in power harvesting capacity is obtained. The output power of this generator is improved by 9.47% which is by far better result as compared to the existing literature.

Adaptive Robust Fault-Tolerant Control Design for Wind Turbines Subject to Pitch Actuator Faults

This paper proposes an adaptive fault tolerant control (FTC) design for a variable speed wind turbine (WT) operating in the high wind speeds region. It aims at mitigating pitch actuator faults and regulating the generator power to its rated value, thereby reducing the mechanical stress in the high wind speeds region. The proposed FTC design implements a sliding mode control (SMC) approach with an adaptation law that estimates the upper bounds of the uncertainties. System stability and uniform boundedness of the outputs was proven using the Lyapunov stability theory. The proposed approach was validated on a 5 MW three-blade wind turbine modeled using the National Renewable Energy Laboratory’s (NREL) Fatigue, Aerodynamics, Structures and Turbulence (FAST) wind turbine simulator. The controller’s performance was assessed in the presence of several pitch actuator faults and turbulent wind conditions. Its performance was also compared to that of a standard SMC approach. Mitigation of blade pitch actuator faults, generation of uniform power, smoother pitching actions and reduced chattering compared to standard SMC approach are among the main features of the proposed design.

Upwind Horizontal Axis Wind Turbine Output Power Optimization via Artificial Intelligent Control System

Power capturing capacity is one of the key performance indicators of wind turbines. This article presents a study done on the optimization of output power of upwind horizontal axis wind turbine using artificially intelligent control system. The study shows how blade tip speed ratio (λ) and pitch angle (β) are optimized to increase wind turbines power conversion coefficient (C_p) which increases the output power. An artificial intelligence system named Mandani fuzzy inference system (MFIS) was applied to optimize the power conversion coefficient in combination with blade pitch actuator control. To this end, a novel optimization technique is designed that maximizes the power harvesting ability of wind turbines by updating the parameters of the membership functions of fuzzy logic found in the MFIS. With the application of this optimization method, a power conversion coefficient C_p of 0.5608 value is achieved at optimal values of λ and β. As a result, the energy harvesting ability of the wind turbine considered is improved by 16.74%. This study clearly shows that the wind energy harvesting capacity of wind turbines can be enhanced via optimization techniques that could be further implemented in wind turbine blade pitch drive system. Thus, this novel optimization method creates further insights for the wind energy industry in reducing the cost of energy generation.

Design Optimization of Spar Floating Wind Turbines Considering Different Control Strategies

One of the challenges related to the design of floating wind turbines (FWTs) is the strong interactions between the controller and the support structure, which may result in an unstable system. Several control strategies have been proposed to improve the dynamic behaviour, all of which result in trade-offs between structural loads, rotor speed variation, and blade pitch actuator use, which makes controller design a challenging task. Due to the interactions, simultaneous design of the controller and support structure should be performed to properly identify and compare different solutions. In the present work, integrated design optimization of the blade-pitch controller and support structure is performed for a 10 MW spar FWT, considering four different control strategies, to evaluate the effect of the controller on the structural design and associated costs. The introduction of velocity feedback control reduces the platform pitch response and consequently the fatigue loads in the tower, which leads to a decrease in the tower costs compared to a simple PI controller. Low-pass filtering of the nacelle velocity signal to remove the wave-frequency components results in reduced rotor speed variation, but offers only small improvements in costs, likely due to the limited wave-frequency response for the considered designs. Comparisons with nonlinear time-domain simulations show that the linearized model is able to capture trends with acceptable accuracy, but that significant overpredictions may occur for the platform pitch response.

Fault-Tolerant Individual Pitch Control for Load Mitigation in Wind Turbines With Actuator Faults

The sizes of wind turbines have been steadily increasing over the past decade, especially on offshore sites. The greater structural flexibility of such machines necessitates the development of reliable load mitigation techniques to alleviate the effects of asymmetric wind loads and fatigue. Given the importance of such techniques, this article proposes a reliable load mitigation scheme, referred to as “fault-tolerant individual pitch control,” for individually adjusting the pitch angle of wind turbine blades in the presence of blade pitch actuator faults. The proposed scheme consists of a collective pitch control augmented with an individual pitch control, and a fault detection and diagnosis system. Simulation results using an offshore wind turbine illustrate the effectiveness as well as fault-tolerance capability of the developed scheme compared to controlling the pitch angles collectively. The developed scheme not only ensures an almost equal output power with reduced loads on the turbine, but also tolerates the effects of possible faults in pitch actuators of the blades.

Nonlinear model predictive control to reduce pitch actuation of floating offshore wind turbines

Modern-day wind turbines use active pitch control to reduce mechanical loads on the turbines in addition to regulating generator power. These control algorithms increase blade pitch actuation, primarily to reduce the 1P (once per revolution) component of the aerodynamic load. However, it is also known that the failure of the blade pitch system is a significant source of turbine downtime. Control algorithms that increase pitch actuation will only add to this problem. Therefore, increasing blade pitch actuation to reduce mechanical loads may not be the best solution is every situation. Hence, in this paper, an individual pitch control strategy is proposed to reduce pitch actuation without deteriorating rotor speed regulation or increasing structural vibrations. The controller is developed under a Non-linear Model Predictive Control (NMPC) framework. It is assumed that a preview of the inflow wind field is available in the form of LIDAR (LIght Detection And Ranging) wind speed measurements. The results presented in this paper show that it is possible to reduce blade pitch actuation below the baseline level while maintaining rated rotor speed.

Numerical modeling of the hydraulic blade pitch actuator in a spar‐type floating wind turbine considering fault conditions and their effects on global dynamic responses

AbstractThis paper deals with numerical modeling of the hydraulic blade pitch actuator and its effect on the dynamic responses of a floating spar‐type wind turbine under valve fault conditions. A spar‐type floating wind turbine concept is modeled and simulated using an aero‐hydro‐servo‐elastic simulation tool (Simo‐Riflex [SR]). Because the blade pitch system has the highest failure rate, a numerical model of the hydraulic blade pitch actuator with/without valve faults is developed and linked to SR to study the effects of faults on global responses of the spar‐type floating wind turbine for different faults, fault magnitudes, and environmental conditions. The consequence of valve faults in the pitch actuator is that the blade cannot be pitched to the desired angle, so there may be a delay in the response due to excessive friction and the wrong voltage, or slit lock may cause runaway blade pitch. A short circuit may cause the blade to get stuck at a particular pitch angle. These faults contribute to rotor imbalance, which result in different effects on the turbine structure and the platform motions. The proposed method for combining global and hydraulic actuator models is demonstrated in case studies with stochastic wind and wave conditions and different types of valve faults.

Linear Quadratic Optimal Control of a Spar-Type Floating Offshore Wind Turbine in the Presence of Turbulent Wind and Different Sea States

This paper presents the design of a linear quadratic (LQ) optimal controller for a spar-type floating offshore wind turbine (FOWT). The FOWT is exposed to different sea states and constant wind turbulence intensity above rated wind speed. A new LQ control objective is specified for the floater-turbine coupled control, in accordance with standard requirements, to reduce both rotor speed fluctuations and floater pitch motion in each relevant sea state compared with a baseline proportional-integral (PI) controller. The LQ weighting matrices are selected using time series of the wind/wave disturbances generated for the relevant sea states. A linearized state-space model is developed, including the floater surge/pitch motions, rotor speed, collective blade pitch actuation, and unmeasured environmental disturbances. The wind disturbance modeling is based on the Kaimal spectrum and aerodynamic thrust/torque coefficients. The wave disturbance modeling is based on the Pierson–Moskowitz spectrum and linearized Morison equation. A high-fidelity FOWT simulator is used to verify the control-oriented model. The simulation results for the OC3-Hywind FOWT subjected to turbulent wind show that a single LQ controller can yield both rotor speed fluctuation reduction of 32–72% and floater pitch motion reduction of 22–44% in moderate to very rough sea states compared with the baseline PI controller.

Yaw motion of floating wind turbine platforms induced by pitch actuator fault in storm conditions

The paper discusses the factors affecting the large amplitude yaw responses of the DeepCwind wind turbine platform in storms with a faulty blade pitch actuator. The behaviour in operational and storm conditions without faults is provided as a base of comparison. They are followed by the responses to 50-year extreme values defined by the IEC standards, North Sea statistics, and Portugal's coastal storm data. All environmental conditions are head waves upwind sets, presumably causing minimal yaw excitation despite differing in wave excitation frequencies and maximum wind speeds. These scenarios are expanded further to cases where one of the pitch actuators stops functioning and fails to feather the blade. The result reveals large angle yaw motions of the platform. The reasoning behind this motion is explained and a possible method of mitigation through a revision of the HSS brake capacity is discussed. In this process, a frequently applied form of the hydrostatic matrix is reviewed as it includes overlooked coupling terms.

Fault-Tolerant Individual Pitch Control of a Wind Turbine with Actuator Faults

The sizes of wind turbines have been steadily increasing over the past decade, especially on the offshore sites. The greater structural flexibility of such machines necessitates considerations of reliable load mitigation techniques in order to alleviate the effects of asymmetric wind loads and fatigue. This paper proposes a reliable load mitigation scheme, referred to as ‘fault-tolerant individual pitch control’, which involves adjustments in pitch angles of the wind turbine blades individually in the presence of blade pitch actuator faults. The proposed scheme consists of a collective pitch control augmented with an individual pitch control, and a fault detection and diagnosis system. Simulation results obtained for a large-scale offshore wind turbine with a stochastic wind field illustrate effectiveness as well as fault-tolerance of the proposed scheme compared to the scheme based on control of pitch angles collectively. Moreover, the proposed scheme not only ensures more uniform output power with reduced loads on the turbine, but also tolerates the effects of possible faults in pith actuators of the blades.

Evaluation of a wind speed estimator for effective hub-height and shear components

Estimates of the effective wind speed disturbances acting on a wind turbine are useful in a variety of control applications. With some simplifications, it is shown that for zero yaw error, any wind field interacting with a turbine can be equivalently described using a hub-height (uniform) component as well as linear horizontal and vertical shear components. A Kalman filter-based wind speed estimator is presented for estimation of these effective hub-height and shear components. The wind speed estimator is evaluated in the frequency domain using the FAST aeroelastic simulator with the National Renewable Energy Laboratory's 5 MW reference wind turbine model and realistic hub-height and shear disturbances. In addition, the impact of the inflow model, used to simulate the rotor aerodynamics, on the Kalman filter performance is investigated. It is found that the estimator accuracy strongly depends on the inflow model used. In general, the estimator performs well up to a bandwidth of 1 Hz when the inflow model used for simulation matches the model used to create the linear Kalman filter model and blade pitch angle remains close to the linearization operating point. However, inaccuracies in the linear model of the turbine when dynamic inflow is used for simulation as well as nonlinearities in the turbine dynamics due to blade pitch actuation cause performance to degrade. Finally, the improvement gained by employing a non-causal wind speed estimator is assessed, showing a minor increase in performance. Copyright © 2014 John Wiley & Sons, Ltd.

Parallel Blade-Vortex Interaction Modelling for Helicopter Rotor Noise Control Synthesis

The present work deals with a methodology for the alleviation of loads and corresponding emitted noise generated by blade-vortex interaction (BVI) phenomena occurring on helicopter main rotors in low-speed, descent flight. It consists of a multi-cyclic, optimal control approach driving higher harmonic blade pitch actuation. First, for the specific flight condition to be examined, the BVI phenomena are simulated as equivalent two-dimensional, multi-vortex, parallel BVI problems and then a local controller methodology is applied for the efficient identification of the closed-loop control algorithm. In order to assess the capability of the proposed control approach to alleviate rotor blade loads and emitted noise, the results of a numerical investigation concerning a realistic helicopter main rotor in descent flight are presented and discussed.

The impact of passive tuned mass dampers and wind–wave misalignment on offshore wind turbine loads

Offshore wind turbines experience complex external loading from a variety of sources, especially wind and waves. To be economical, offshore wind turbine must operate reliably under these loading conditions. The external loading is complicated by the directionality of the wind and the waves. Metocean data in Europe and the US shows that the wind and the waves are often misaligned by significant amounts. This misalignment causes large loads on the tower in the side-side direction, which has very little structural damping compared to the fore-aft direction. Recent papers have highlighted the importance of considering wind–wave misalignment when analyzing the loads of offshore wind turbines. A variety of approaches are feasible and have been investigated to mitigate loading on offshore wind turbines due to the wind and waves. Many approaches control the aerodynamic loading on the rotor, either via control of the blade pitch or other aerodynamic actuation. This paper analyzes an alternative approach using structural control, in which passive tuned mass dampers are used to absorb and dissipate structural vibrations. In particular, this study investigates the load mitigation potential of passive tuned-mass-dampers for a 5MW offshore wind turbine supported by a monopile, and subjected to realistic external conditions that include wind–wave misalignment. A comprehensive set of operational simulations is used to demonstrate that optimally tuned passive tuned-mass-dampers are capable or reducing tower fore-aft and side-side fatigue loads by approximately 5% and 40%, respectively. A discussion of the practical feasibility of such an approach is also provided.

Robust Proactive Control of Wind Turbines with Reduced Blade Pitch Actuation

A new simultaneous speed and pitch control of wind turbines with the preview measurements and look-ahead calculations is considered. The desired piecewise constant pitch angle profile which is calculated using turbine load prediction, allows the reduction of pitch actuation that in turn, increases the lifetime of actuator. The robust collective pitch control architecture with the maximum possible actuation rate is proposed.Moreover, a new postprocessing technique that provides the high quality estimate of the turbine inertia moment is also described. The results are confirmed by simulation with a wind speed record from the Hönö turbine located outside Gothenburg, Sweden.

Multibody simulation of a generalized predictive controller for tiltrotor active aeroelastic control

A generalized predictive control has been developed for the control of the aeroelasticity and structural dynamics of a tiltrotor. Adaptivity is the key feature of the proposed technique. It gives the controller the capability to autonomously follow the variations of the system. A comprehensive simulation system has been adopted to design and test the adaptive regulator under realistic conditions. The aeroservoelastic tiltrotor has been modelled using a multibody approach, considering the structural dynamics, the aerodynamics, the blade pitch control system kinematics, and actuator and sensor dynamics. Numerical simulations illustrate the capability of the adaptive controller to reduce wing vibrations and loads while significantly extending the flutter-free flight envelope. This controller shows satisfactory performances within the whole flight envelope as it is able to properly work in different rotor trim conditions and varying structural properties in the presence of external disturbances and measurement noise.