NREL Wind Turbine Research Articles

An Efficient Computational Analysis and Modelling of Transferred Aerodynamic Loading on Direct-Drive System of 5 MW Wind Turbine and Results Driven Optimisation for a Sustainable Generator Structure

The study presents an efficient computational investigation on the behaviour of the direct-drive system integrated into the offshore 5 MW NREL wind turbine model under demanding aerodynamic loading conditions with the aim of optimising and developing more sustainable key structural components. The research was based on computational simulation packages in order to verify the use of real-world wind data and the loading conditions on the blade structures through aero-elastic simulation studies as well as analyse the behaviour of the drive system. Through the application of validated aerodynamic loading conditions, resulting normal forces on the blades structure were obtained and applied to a dedicated simplified model that was also previously validated to estimate the transferred loads into the powertrain. The adopted methodology allowed for the identification of shaft misalignment induced air gap eccentricity. The impact of shaft deflections on resulting magnetomotive force was considered by making use of the Maxwell stress distribution expression. By taking into account the resulting loading cases on the generator structure, as well as the inherent typical loads generated by the electrical machine, a procedure including structural parametric and topology optimisation was developed and performed, achieving a rotor mass reduction between 8.5 and 9.6% compared to the original model.

Incidence of wind spectrum and turbulence intensity on the design of mooring systems for floating offshore wind turbines

The paper focuses on the incidence of wind spectrum and turbulence intensity on the design of stationkeeping systems for Floating Offshore Wind Turbines. After a brief review about the employed nonlinear time-domain hydrodynamic model, some basics about the Ultimate and Fatigue Limit State design conditions of the mooring system are provided. Subsequently, the two wind spectra, employed in the numerical simulations, are briefly introduced. The former is the NPD wind spectrum, generally applied for the design of mooring systems for typical offshore structures, employed in the oil and gas sector. The latter is the Kaimal wind spectrum, generally employed for the design of offshore wind turbines in conjunction with different turbulence models, depending on the operative scenario. The numerical investigation is performed considering the DeepCwind platform, equipped with the 5 MW NREL wind turbine, as reference support structure, deployed in the North Sea area. Three different water depths, from 200 up to 400 m, are considered. It is verified that both the wind spectrum and turbulence model play a fundamental role not only for the optimum design of the stationkeeping system, but also for the proper selection of the line scope, as well as of the leading usage factors.

Robust Reinforcement Learning-Based Multiple Inputs and Multiple Outputs Controller for Wind Turbines

The control of variable-speed wind turbines that generate electricity from the kinetic energy of the wind involves subsystems that need to be controlled simultaneously, namely, the blade pitch angle controllers and the generator torque controllers. The presented study solves the control problem with multiple inputs and multiple outputs (MIMO), using the method of reinforcement learning–based Trust Region Policy Optimization, through which the control parameters of both subsystems are simultaneously optimized. In this case, the robust control problem is transformed into a constrained optimal control problem with an appropriate choice of value functions for the nominal system. The study aims to synthesize a robust controller, with the aim of maximizing the generated energy (power) and minimizing unwanted forces (thrust). The innovative control architecture uses an extended input space, which allows fine-tuning of parameters for each operating state. Test calculations carried out in simulation experiments using models of the 5 MW NREL wind turbine and the 4 MW Enercon E-126 EP3 wind turbine are presented to illustrate the performance and practicality of the proposed approach.

Inverse modeling of wind turbine drivetrain from numerical data using Bayesian inference

Wind turbine drivetrain systems experience occasional failure in their operational life-time. Dynamic loads in these systems often differ from those predicted in the design phase, which may lead to incipient faults and damage eventually resulting to unpredicted failures. Faults in a system cause changes in the system dynamic properties. Therefore, a calibrated dynamic model can be used for fault diagnosis of the drivetrain system. The current paper implements a Bayesian inference method for physics-based model updating for the first time to estimate the parameters of a physics-based wind turbine drivetrain model as well as the unknown input loads using measurement data. An information-theoretic approach is adopted to study the identifiability of different model parameters given different subsets of drivetrain measurements. The 5 MW NREL wind turbine is used as a case study, and its drivetrain is modeled by a 5-mass torsional model. Torsional shaft stiffnesses and rotor mass moment of inertia are the parameters reflecting dynamics of the drivetrain and are assumed unknown. Moreover, the aerodynamics input torque applied to the drivetrain system is assumed as unknown. The Bayesian inference method is used to estimate jointly the unknown model parameters and aerodynamic input torque using numerically simulated measurement data. The case studies show that the proposed model updating approach can accurately estimate the low-speed shaft stiffness, rotor mass moment of inertia, and the time history of aerodynamic torque jointly using only measurements from the generator including generator torque and rotational speed.

Wind power plant grid-forming control and influences on the power train and power system oscillations

In future power systems, wind power plants are supposed to contribute in the voltage and frequency stability of the grid. For this purpose, the control strategy of the wind power-frequency converter system needs to change from grid-following to grid-forming control. In this paper, the influence of future wind power plants equipped with the grid-forming control strategy on the wind turbine itself and the power system oscillations is studied. For this purpose, the coupled model of wind power plant and a relatively realistic model of future power system is employed, which is able to capture the internal dynamics of wind turbine power train system and its dynamic interactions with the rest of power system. It is shown how wind power plant local- and inter-area oscillations can influence/be influenced by the power system if insufficient damping is presented by wind turbines' power train system. It is shown how the variation of demand in the power grid can consistently excite wind turbine local- and inter-area modes which can cause undamped oscillations in both wind turbine power train system and the rest of power system if insufficient damping is provided by the wind turbine power train system. A test case, using 1.5 MW NREL wind turbine drivetrain, is demonstrated.

A novel Nonlinear Model Predictive Controller for Power Maximization on Floating Offshore Wind Turbines

Reducing the Levelized Cost of Energy is the main objective of wind turbine industry, in particular for the emerging sector of floating offshore turbines. In this work, a novel Economic Nonlinear Model Predictive Control (ENMPC) strategy is developed to maximize the power production of floating offshore wind turbines. The control problem is solved through an indirect method, which achieves the computational efficiency required to apply it in real world cases. A non-linear Reduced Order Model of the floating turbine predicts aerodynamic power, generator temperature and platform motions inside the controller. A set of constraints, including a bound on the generator temperature, the thrust and platform velocities are imposed. Simulations using the open-source engineering tool OpenFAST on the 5MW NREL wind turbine supported by the OC3 spar buoy platform [1] are performed to validate the turbine model and then to assess the controller performances in realistic wind and sea state conditions. With respect to the standard controller, a 4.3% increase of generated power in rated conditions is achieved with a more stable generator temperature.

Predictive capability of actuator disk models for wakes of different wind turbine designs

To evaluate the predictive capability of the actuator disk (AD) models in simulating wakes of different wind turbine designs, we compare the results of the AD simulation with those of the actuator surface (AS) simulation for the EOLOS, NREL and a variant of the NREL (i.e., NREL-V) wind turbine designs. Two types of AD models are considered, i.e., the AD-R and AD-NR models corresponding to the AD model with and without rotational effects, respectively. For the AD models, the force coefficients are both obtained from the corresponding AS simulations. The results from the AD simulation are compared with those of AS simulations. It is observed that the velocity profiles predicted by the AD models agree well with the AS predictions. For the turbulent kinetic energy and the Reynolds shear stress, differences appear at far wake locations (7D, and 9D downwind of the turbine where D is the rotor diameter) for both the EOLOS and the NREL-V turbines. In case of the NREL turbine, on the other hand, there is an overall good agreement except in 3D downwind to the turbine. Furthermore, the modes obtained by using the proper orthogonal decomposition from the AD and AS simulations are also presented and compared with each other, indicating that the distribution of the mode energy, and the location and features of the mode patterns differ for different turbine designs.

Fatigue Assessment of Moorings for Floating Offshore Wind Turbines by Advanced Spectral Analysis Methods

The fatigue assessment of mooring lines for floating offshore wind turbines represents a challenging issue not only for the reliable design of the stationkeeping system but also for the economic impact on the installation and maintenance costs over the entire lifetime of the offshore wind farm. After a brief review about the state-of-art, the nonlinear time-domain hydrodynamic model of floating offshore wind turbines moored by chain cables is discussed. Subsequently, the assessment of the fatigue damage in the mooring lines is outlined, focusing on the combined-spectrum approach. The relevant fatigue parameters, due to the low- and wave-frequency components of the stress process, are estimated by two different methods. The former is based on the time-domain analysis of the filtered stress process time history. The latter, instead, is based on the spectral analysis of the stress process by two advanced methods, namely the Welch and Thomson ones. Subsequently, a benchmark study is performed, assuming as reference floating offshore wind turbine the OC4-DeepCWind semisubmersible platform, equipped with the 5 MW NREL wind turbine. The cumulative fatigue damage is determined for eight load conditions, including both power production and parked wind turbine situations. A comparative analysis between time-domain and spectral analysis methods is also performed. Current results clearly show that the endorsement of advanced spectral analysis methods can be helpful to improve the reliability of the fatigue life assessment of mooring lines.

Comparative study among non-redundant and redundant stationkeeping systems for floating offshore wind turbines on intermediate water depth

The paper focuses on the design and selection of mooring systems for Floating Offshore Wind Turbines, deployed on intermediate water depths, and provides a comparative analysis among non-redundant and redundant layouts, consisting of 3 and 9 lines, respectively. After developing the non-linear time-domain hydrodynamic model, the Ultimate, Accidental and Fatigue Limit State Design Conditions for mooring systems are briefly discussed. Subsequently, an improved optimization procedure, devoted to detect the minimum weight configuration of the mooring system, constrained to the fulfilment of several restraint criteria, is outlined and applied to a reference case study. The OC4-DeepCwind semisubmersible tri-floater platform, equipped with the 5 MW NREL wind turbine, is assumed to be deployed in the Northern North Sea. The optimization procedure is embodied to preliminarily detect a set of candidate configurations, satisfying the Ultimate and Accidental Limit State design conditions, that are subsequently checked to assess the expected fatigue life. The preliminarily design of anchor foundations is also performed. Finally, a cost analysis is carried out to investigate the impact of the line number on the total installation costs of the stationkeeping system. Some considerations, concerning the impact of line number on the expected cost due to maintenance operations, are also provided.

Asymmetrical Load Mitigation of Wind Turbine Pitch Actuator Faults using Unknown Input-based Fault-tolerant Control

Offshore wind turbines suffer from asymmetrical blade loading, resulting in enhanced structural fatigue. Individual pitch control (IPC) is an effective method to achieve blade load mitigation, accompanied by enhancing the pitch movements and thus increased the probability of pitch actuator faults. The occurrence of faults will deteriorate the IPC load mitigation performance, which requires fault-tolerant control (FTC). IPC is itself analogous to the FTC problem because the action of rotor bending can be considered as a fault effect. Therefore, the work thus proposes a "co-design" strategy, constituting a combination of IPC-based asymmetrical load mitigation combined with FTC acting at the pitch system level. The FTC uses the well-known fault estimation and compensation strategy. A Proportional-Integral Pi-based IPC strategy for blade mitigation is proposed in which the robust fault estimation is achieved using a robust unknown input observer (UIO). The performance of two pitch controllers (baseline pitch controller, Pi-based IPC) are compared in the presence of pitch actuator faults (including low pressure & loss of effectiveness). The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system.

Wind Turbine Drivetrain Expert Fault Detection System: Multivariate Empirical Mode Decomposition based Multi-sensor Fusion with Bayesian Learning Classification

To enhance the predictive condition-based maintenance (CBMS), a reliable automatic Drivetrain fault detection technique based on vibration monitoring is proposed. Accelerometer sensors are mounted on a wind turbine drivetrain at different spatial locations to measure the vibration from multiple vibration sources. In this work, multi-channel signals are fused and monocomponent modes of oscillation are reconstructed by the Multivariate Empirical Mode Decomposition (MEMD) Technique. Noise assisted methodology is adapted to palliate the mixing of modes with common frequency scales. The instantaneous amplitude envelope and instantaneous frequency are estimated with the Hilbert transform. Low order and high order statistical moments, signal feature descriptors and randomness measures (entropy) are extracted as truthful features. The feature set is fed into the Bayes classifiers to compare the detection performance. From the analysis it is found that the proposed method is well performed with the Dynamic Bayes Belief Network Classifier showing the detection accuracy of 97.69%. To validate the results, the NRELWind Turbine Drivetrain benchmarking dataset is used.

Fault-tolerant Individual Pitch Control using Adaptive Sliding Mode Observer

Due to the increasing size of wind turbines, the unbalanced loads caused by the uneven spatial distribution of wind speed and turbulence are becoming larger and larger. As has been proved, individual pitch control (IPC) can mitigate the blade asymmetric loads greatly in region 3. On the other hand, the pitch actuator faults can affect the pitching performance with slow dynamics, resulting in generator power instability and even deteriorating the unbalanced loads of blades. However, the effects of unbalanced blade loads deterioration caused by pitch actuator faults have not been taken into account by the traditional IPC design. In the present paper, a fault-tolerant control (FTC) strategy using adaptive sliding mode estimation is combined with a traditional IPC system based on two different control methods (Proportional-Integral and H∞ loop-shaping). It maintains the nominal pitch performance and removes the negative effects of pitch actuator faults on generator power and unbalanced blade loads perfectly. The effectiveness of the proposed strategy is verified on the 5MW NREL wind turbine system.

Parabolic RANS solver for low‐computational‐cost simulations of wind turbine wakes

AbstractA numerical framework for simulations of wake interactions associated with a wind turbine column is presented. A Reynolds‐averaged Navier‐Stokes (RANS) solver is developed for axisymmetric wake flows using parabolic and boundary‐layer approximations to reduce computational cost while capturing the essential wake physics. Turbulence effects on downstream evolution of the time‐averaged wake velocity field are taken into account through Boussinesq hypothesis and a mixing length model, which is only a function of the streamwise location. The calibration of the turbulence closure model is performed through wake turbulence statistics obtained from large‐eddy simulations of wind turbine wakes. This strategy ensures capturing the proper wake mixing level for a given incoming turbulence and turbine operating condition and, thus, accurately estimating the wake velocity field. The power capture from turbines is mimicked as a forcing in the RANS equations through the actuator disk model with rotation. The RANS simulations of the wake velocity field associated with an isolated 5‐MW NREL wind turbine operating with different tip speed ratios and turbulence intensity of the incoming wind agree well with the analogous velocity data obtained through high‐fidelity large‐eddy simulations. Furthermore, different cases of columns of wind turbines operating with different tip speed ratios and downstream spacing are also simulated with great accuracy. Therefore, the proposed RANS solver is a powerful tool for simulations of wind turbine wakes tailored for optimization problems, where a good trade‐off between accuracy and low‐computational cost is desirable.

A correlation-based algebraic transition model

A correlation-based algebraic transition model that relies on local flow information is proposed. The model is qualified as an algebraic model, or a zero-equation model since it includes an intermittency function in place of an intermittency equation that is found in one- or two-equation models. The basic idea behind the model is that, instead of deriving new equations for intermittency transport, existing transport terms of the Spalart–Allmaras (S-A) turbulence model can be used. To this end, the production term of the S-A model is multiplied with the proposed intermittency function γBC; thereby the turbulence production is damped until it satisfies some turbulence onset requirements. The proposed formulation also depends on local information that uses empirical correlations to detect the transition onset using less equations and less calibration constants than other higher order models. The model is first validated against some widely-used zero and variable pressure gradient flat plate test cases with quite successful results. Second, the model is employed for some low Reynolds number airfoil cases with very promising results. Third, the model is applied for a turbine cascade case with success. Finally, two different three-dimensional wing flow cases were calculated under transonic and low subsonic flow conditions. To this end, the DLR-F5 wing subject to a transonic Mach number of 0.82 and the low-speed NREL wind turbine flow case are simulated and good agreement with experiments are observed. The results indicate that the proposed model may become an alternative for other models as it uses less computational resources with equivalent or higher accuracy characteristics that is quite advantageous for the computational fluid dynamics design in industry.

Mooring design and selection for floating offshore wind turbines on intermediate and deep water depths

The paper focuses on design and selection of mooring systems for Floating Offshore Wind Turbines (FOWTs) for intermediate and deep water depths, based on ultimate, accidental and fatigue limit state design conditions, with reference to power production, parked wind turbine and mooring line fault conditions. Platform static and dynamic offsets are determined by a purposely developed 6DOF programme in the frequency domain, accounting for first and second order motions. The Dutch tri-floater platform, together with the well-known 5 MW NREL wind turbine, is assumed as reference design. Besides, two sites, the one in the Southern North Sea, near Dogger Bank on water depths ranging from 50 up to 80 m, the other one in the Northern North Sea, near the Troll field area on water depths ranging from 200 up to 350 m, are assumed as candidate deployment areas, to investigate the effect of: (i) line number, (ii) platform admissible offset and line scope, (iii) offshore/onshore planned maintenance inspections and (iv) mooring technology on relevant installation and maintenance costs. A preliminary cost analysis is also performed and some recommendations are given to correctly choice the most suitable mooring configuration, as a function of water depth.

Turbulence Model Prediction Capability in 2D Airfoil of NREL Wind Turbine Blade at Stall and Post Stall Region

Turbulence Model Prediction Capability in 2D Airfoil of NREL Wind Turbine Blade at Stall and Post Stall Region

A Study on Aerodynamics from the NREL Wind Turbine by CFD

Studies on the wind turbine has been attempted because not only its mechanical performance but also acoustic noise becomes important issue. Regarding numerical modeling and simulation, researchers must precisely evaluate aerodynamic phenomena on limited memory and CPU resource. This paper presents several preliminary results from simulation of the NREL phase VI wind turbine, using a 3D-CFD-RANS turbulence model, and shows the comparisons of CFD results with experimental results about pressure coefficient on a blade in the case the wind speed is 5m/s. This comparisons are made in the blade with 0° yaw angle, 3° tip pitch angle and 72 rpm (test sequence S).

Fragility analysis of a 5-MW NREL wind turbine considering aero-elastic and seismic interaction using finite element method

With the improvements and advances made in the field of renewable energy, this alternative method has become competitive with more traditional sources of energy generation techniques, including hydro power or fossil fuels. This has led to construction of wind turbines in areas prone to seismic activity. To increase the power production from wind energy, wind turbines have increased in size and mass, which makes them more vulnerable to lateral loads such as seismic induced forces, wind loads, and in the case of offshore wind turbines, wave loads. For this reason, computational analysis in the field are recently focusing on considering the interaction between lateral loads to present more realistic and cost effective designs. In this paper, the nonlinear dynamic behavior of a 5-MW NREL wind turbine is evaluated considering different earthquake and wind intensities using a newly developed finite element model. The model is first calibrated and verified with simplified models using modal and static pushover analysis. Engineering demand parameters (EDP) and intensity measures (IM) are then obtained from nonlinear incremental dynamic analysis (IDA) and used to assess the probability of exceeding different damage states (DS) using fragility curves. From the findings in this research, it is shown that earthquake loads have considerable effects on the design and analysis of wind turbines.

Aeroelastic analysis of wind turbines using a tightly coupled CFD–CSD method

This paper presents aeroelastic analyses of wind turbines, using the compressible flow Helicopter Multi-Block (HMB2) solver of Liverpool University, coupled with a Computational Structural Dynamics method. For this study, the MEXICO and NREL Phase VI wind turbines were employed. A static aeroelastic method was first employed for the analysis of the MEXICO blade and the effect of the torsional stiffness was studied at 10, 15 and 24m/s axial wind speeds. The torsional deformations showed strong dependency on this parameter and the blade region from mid-span to the tip was the most susceptible to aeroelastic effects. The work progressed by studying both the static and dynamic response on the NREL wind turbine, where the nacelle and the tower were considered. Mean deflections between the static and dynamic methods showed consistency and, due to the structural properties of this blade, flapping modes were dominant. The dynamic aeroelastic method enabled an assessment of the effect of flapping on the blade loads, in conjunction with the effect of tower. Aeroelastic effects were found to be secondary for the MEXICO blade, but had a stronger effect on the larger NREL Phase VI blade.

Development and application of a dynamic stall model for rotating wind turbine blades

In unsteady conditions of wind turbines, both the dynamic stall phenomenon and the three-dimensional (3D) rotational effect affect the rotor aerodynamics. The dynamic stall mechanism for rotating wind turbine blades is first investigated. Through the comparison of the aerodynamic data between the rotating blade and the two-dimensional (2D) airfoil, the normal force slope in the attached flow and the separation point expression in the separated flow are modified in the Beddoes-Leishman (B-L) dynamic stall model for rotating NREL wind turbine blades. The modified model is validated by the comparison between the calculation results and the experimental results of the lift and drag coefficients at different radial positions. Both the hysteresis loop shapes and the calculation values are closer to the experiment than the 2D dynamic stall model. The present dynamic stall model is then coupled to a free vortex wake model. The coupled model is used to calculate the unsteady blade aerodynamic loads and the low speed shaft torque of the NREL wind turbine in a yawed condition. The accuracy is greatly improved by the corrections presented in the paper.