MW Wind Turbine Research Articles

Stochastic Model Predictive Control Based on Polynomial Chaos Expansion With Application to Wind Energy Conversion Systems

The wind energy conversion system (WECS) has a complex structure, and its state space model is highly nonlinear. Due to the random uncertainty of wind speed, it poses a huge challenge to achieve optimal control tasks and ensure the safe and stable operation of the system. Therefore, this article proposes a stochastic model predictive control strategy based on Polynomial Chaotic Expansion (PCE), which achieves the control tasks of MPPT and constant power regions in wind energy conversion systems. Firstly, a simple algorithm is proposed to obtain a set of basis functions that are suitable for the stochastic variable wind speed. Then, the obtained basis functions are used to propagate the uncertainty of the original uncertain differential equation of the wind energy conversion system through polynomial chaotic expansion. Combining the operating region and constraint conditions of the wind energy conversion system, the original stochastic uncertainty problem is transformed into a deterministic convex optimization problem. Using NREL 5MW wind turbine as the research object for simulation, the task of capturing maximum wind energy in MPPT area and tracking rated power points in constant power area was achieved. The experimental results show that the proposed control method can effectively improve the wind energy capture capability and achieve accurate tracking of output power to rated power.

Dynamic analysis of an improved shared moorings for floating offshore wind farm

Shared mooring lines have demonstrated their effectiveness in reducing the installation costs of floating offshore wind farms by minimizing the requirement for multiple anchors. However, this innovation has also brought complex restoring properties and a greater tendency towards resonance. To tackle this challenge, this research presents a novel approach for shared mooring systems, implemented in a 2 × 2 orthogonal wind farm arrangement featuring 5 MW wind turbines installed on the Barge platform. Through the application of FAST and AQWA, a comparative analysis is conducted juxtaposing the original mooring (OM) and three new mooring models, namely buoy mooring (BM), clump weight mooring (WM) and buoy clump weight mooring (BWM). A comprehensive examination is carried out to assess the impact of on platform and mooring characteristics. The results show that the BM can effectively reduce the platform's surge and sway response, and that the mooring tension and laid length decrease as the net buoyancy increases. The WM increases the response amplitude at the yaw direction. The BWM with link buoys helps to improve the dynamic response of the platform and increases the length of the mooring laid. This analysis provides valuable insights for the design of floating wind farms incorporating shared mooring systems.

Exploratory Study on the Application of Graphene Platelet-Reinforced Composite to Wind Turbine Blade.

With the growth of the wind energy market and the increase in the size of wind turbines, the demand for advanced composite materials with high strength and low density for wind turbine blades has become imperative. Graphene platelets (GPLs) stand out as highly premising reinforcements due to their exceptional physical properties, resulting in their widespread adoption in the composite industry in recent years. The present study aims to analyze the applicability of a graphene-platelet-reinforced composite (GPLRC) to wind turbine blades in terms of structural performance. A finite element blade model is constructed by referring to the National Renewable Energy Laboratory (NREL) 5 MW wind turbine, and its reliability is verified through a convergence test. The performance of the wind turbine blade is quantitatively examined in terms of the deflection and stress, natural frequencies, and twist angle. The applicability of the GPL-reinforced wind blade is explored through a comparison with wind blades manufactured with glass fiber and carbon nanotubes (CNTs). The comparison indicates that the performance of a wind blade can be remarkably improved by reinforcing with GPLs instead of traditional fillers, and the weight of not only the wind blade itself but also the wind turbine system can be remarkably reduced. The present results can be useful in the development of next-generation high-strength lightweight wind turbine blades.

Efficiently solving large-scale electrostatic lightning problems by integrating characteristic basis functions into boundary element method

The evaluation of the electric field near objects of complex geometries is critical in the pre-bridging regime of lightning strikes in high-voltage transmission systems, which is subject to an open domain problem and can be computationally expensive. In this paper, the characteristic basis function method (CBFM) is incorporated into the conventional boundary element method (BEM) to efficiently handle large-scale electrostatic problems. Within the CBFM, low-level basis functions have been replaced by high-level macro characteristic basis functions, resulting in a significant reduction in the number of degrees of freedom. This reduction in unknowns allows iteration-free direct solvers to approximate the matrices, further reducing the computational complexity of the problem. Numerical examples of the surface charge distribution of an actual 500 kV tower-transmission-line system and a three MW wind turbine in the lightning environment demonstrate the accuracy of the proposed CBFM, while requiring considerably much fewer computational resources compared with conventional BEM. Furthermore, CBFM is highly parallelizable, implying the feasibility of handling large electrostatic lightning problems with complex geometries.

Control of dual star induction generator based on multi-level inverter used in wind energy conversion system

This paper presents vector control of dual star induction generator (DSIG) integrated into variable speed wind energy and supplied by three-level NPC converters. Now the DSIG is the most common among multiphase machines when used in high power generation systems, which is associated with two converters. Maximum power point tracking (MPPT) for extracting a maximum of power fluctuating wind speed is illustrated. In order to decrease the fluctuations that appear in the currents generated by DSIG to the electrical network, we propose the NPC structure three-level inverter. Simulation results of a 1.5 MW Wind turbine are presented to illustrate the validity of this application.

Fault-Tolerant Control of Floating Wind Turbine With Switched Adaptive Sliding Mode Controller

The fast-growing development of floating wind turbines demands control systems capable of both reducing output power fluctuations and fault-tolerant function. In this paper, we propose an adaptive switched sliding mode controller to enhance the performance of floating wind turbine systems in the presence of environmental uncertainties and actuator faults. A control-oriented switched linear model for floating wind turbines is introduced, considering the average dwell time. Based on the proposed controller, a full-order state observer and an adaptive law compensate for the debilitated control outputs resulting from detecting errors, disturbances, and faults. The control parameters are derived by solving stability theorems, which are proved by the Lyapunov stability theory, linear matrix inequality technique, and average dwell time technique. The proposed model and controller are validated on the NREL 5MW wind turbine and spar-buoy platform using the high-fidelity fatigue, aerodynamics, structures, and turbulence (FAST) code. The performance of the proposed controller is compared with an optimal gain-scheduling proportional-integral controller under different wind-wave combined conditions. The results show that the proposed controller improves the power quality and attenuates mechanical loads of floating wind turbine under healthy and faulty conditions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Floating wind turbines have drawn significant interest in renewable energy. When operating in the ocean far from shore, it is of great importance for floating wind turbines to have fault-tolerance capabilities for achieving stable power quality when faults occur in one or more components. A challenging problem is how to mitigate the fault effects on the wind turbine system. This paper proposes an adaptive fault-tolerant control strategy in the case of actuator fault occurrence in floating wind turbines.

The rotor as a sensor – observing shear and veer from the operational data of a large wind turbine

Abstract. This paper demonstrates the observation of wind shear and veer directly from the operational response of a wind turbine equipped with blade load sensors. Two independent neural-based observers, one for shear and one for veer, are first trained using a machine-learning approach and then used to produce estimates of these two wind characteristics from measured blade load harmonics. The study is based on a dataset collected at an experimental test site featuring a highly instrumented 8 MW wind turbine, an IEC-compliant (International Electrotechnical Commission) met mast, and a vertical profiling lidar reaching above the rotor top. The present study reports the first demonstration of the measurement of wind veer with this technology and the first validation of shear and veer with respect to lidar measurements spanning the whole rotor height. Results are presented in terms of correlations, exemplary time histories, and aggregated statistical metrics. Measurements of shear and veer produced by the observers are very similar to the ones obtained with the widely adopted profiling lidar while avoiding its complexity and associated costs.

Risk-informed integrated design optimization for offshore wind farm electrical systems

The present paper develops and presents a risk-informed framework for the design of electrical systems of offshore wind farms. The framework provides a consistent theoretical and methodical basis for the treatment of uncertainties affecting service life performances and accounts for both the direct and indirect consequences related to system failure events. The risk of electrical systems is represented through a probabilistic systems modeling approach in which the states (direct failure, available, and unavailable) of the components and the resulting consequences are duly accounted for. The paper further proposes a risk-informed design optimization framework for offshore wind farm electrical systems (collection and transmission systems). Two risk indicators, the scenario-based net present value, and the robustness index, are formulated and quantified to support decision-making. The proposed framework and associated methods are illustrated through an application example considering an OWF comprised of 57 10MW wind turbines with HVAC transmission.

A bi-level mode decomposition framework for multi-step wind power forecasting using deep neural network

The proportion of wind energy in global energy structure is growing rapidly, promoting the development of wind power forecasting (WPF) technologies to solve the uncertainty and intermittence of wind power generation. However, the nonlinear and stochastic features of wind power time series restrain the accuracy of multi-step prediction performance. A multi-step WPF (MS-WPF) approach based on a time series bi-level empirical mode decomposition (BLEMD) method and BiLSTM neural network is proposed in this paper to improve the WPF accuracy of regional wind power generators. Since the uncertainty is always generated through coupled factors from both wind and weather-to-power conversion, the linearity feature is first introduced as an aspect apart from the frequency in the proposed approach to decompose the wind power time sequence data. The proposed BLEMD introduces Pearson product-moment correlation coefficient to evaluate the linearity of time series and a linearity-based decomposition algorithm is designed accordingly. To further enhance the precision and release computation burdens, a DL-based prediction strategy, including a BiLSTM network, a CNN-BiLSTM network, and a mean weight estimation method are implemented to predict the components separately. The proposed method only relies on local data, greatly reducing the data acquisition and computation cost. The precision of the proposed MS-WPF is verified by a 2.5 kW wind turbine with horizons from 5 s to 30 s, a 1.5 MW wind turbine with horizons from 10 min to 1 h, and a 51 MW wind farm with horizons from 1 h to 6 h. The comparative experimental results with other cutting-edge methods indicated that the proposed MS-WPF has superior prediction accuracy and stable performance for multi-step prediction.

Wake effect impact on the levelized cost of energy in large floating offshore wind farms: A case of study in the northwest of the Iberian Peninsula

With the growing world energy needs, offshore wind farms tend to increase in terms of installed capacity, rated power, and the number of wind turbines. This trajectory leads to higher electricity production losses due to the wake effect between the wind turbines, resulting in an elevated Levelized Cost of Energy. Therefore, it is crucial to estimate this cost for various wind farm designs, involving the application of different distances between the wind turbines, aiming to identify the most cost-effective solutions. In this study these estimates were carried out within a legally designated 1800 km2 area earmarked for offshore wind energy exploitation by the Spanish government, situated at the northwest corner of the Iberian Peninsula, considering 15 MW wind turbines. This region is one of the most promising areas of the Iberian Peninsula and Europe since its wind resource potential for the upcoming years has been classified as outstanding. The wind data employed in this analysis emanates from a dynamical downscaling process performed using the Weather Research and Forecasting model, derived from a multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project. The data encompasses the timeframe spanning 2025 to 2049, under the Shared Socioeconomic Pathways 2–4.5, adjusted to coincide with the projected operational lifetime of wind farms. The results show that, without any kind of restrictions in terms of installed power and number of wind turbines, the most economically advantageous Levelized Cost of Energy is achieved at intermediate distances between the wind turbines. Conversely, when specifying a predetermined number of wind turbines, optimal results are attained with the application of the highest distance between turbines.

Optimal design of a hinge-spring-friction device for enhancing wind induced structural response of onshore wind turbines

Wind turbines are subjected to fluctuating wind loads leading to considerable forces and structural fatigue to the towers, ultimately affecting costs, performances, and lifespan, for the tower as well as for the foundation. To mitigate these issues, both in terms of peak and fatigue structural demand, this paper presents the development and optimization of a Hinge-Spring-Friction Device (HSFD) designed for onshore wind turbines. A decoupled numerical model of the wind turbine system incorporating the HSFD is first established. The wind load is modelled by means of the open-source software QBlade© accounting for different wind conditions. These loads are then applied to a FEM structural model of the wind turbine developed in Simulink© and optimized for computational efficiency. The optimal design parameters (strength and stiffness of the frictional and elastic part, respectively) of the HSFD are determined through a multi-objective constrained optimization algorithm, minimizing the peak base moment and total damage fatigue. The proposed framework is then applied to a NREL 5 MW wind turbine to provide an applicative example. The results show that the optimized HSFD can significantly reduce the fatigue damage and the base moment demand to the tower, so providing a really promising solution for the effective design of wind turbines as well as for the repowering of existing plants.

Impact of incoming turbulence intensity and turbine spacing on output power density: A study with two 5MW offshore wind turbines

Turbulence intensity in offshore environments has significant effects on the performance of offshore wind turbines. To maximize output power of offshore wind turbines within a limited space, i.e., achieving maximum output power density, it is essential to investigate the influences of incoming turbulence intensity and turbine spacing on output power density. The Large Eddy Simulation coupled Actuator Line Method (LES-ALM) is used in this study to simulate two utility-scale NREL-5 MW wind turbines in different turbulent environments and turbine spacings. The optimal incoming turbulence intensity and turbine spacing are identified using an active learning method. The determined optimal parameters act as a benchmark for the impact analysis. The findings indicate that the increase of turbine spacing initially results in a considerable rise in the output power density of the two NREL-5 MW wind turbines, followed by a slight downward trend across various turbulent environments. The increase of the incoming turbulence leads to a steady rise of the output power density when the turbine spacing is less than 5.1D (D is the rotor diameter), while a rise followed by a decrease in the output power density is observed for the turbine spacing exceeding 5.1D. Notably, when the turbine spacing is 5.9D and the reference value of turbulence intensity is 15.2%, the output power density reaches its global maximum.

Study on coupled mode flutter parameters of large wind turbine blades

As the size of wind turbine blades increases, the flexibility of the blades increases. In actual operation, airflow flow can cause aerodynamic elastic instability of the blade structure. Long blades may experience coupled mode flutter due to the bending torsion coupling effect, leading to blade failure. Based on Euler Bernoulli beam theory combined with Theodorsen non directional aerodynamic loads, a blade flutter characteristic equation is established through finite element method. Taking NREL 5 MW wind turbine blades as an example, analyze the influence of parameter changes in different regions of the blades on flutter characteristics. Research has found that paramter changes in the tip region of blade have the greatest impact on flutter characteristics. The vibration frequency shows an overall upward trend with the increase of waving stiffness and torsional stiffness. The flutter velocity of the three regions tends to stabilize as the bending stiffness decreases. The blade flutter speed increases with the increase of torsional stiffness. The radius of gyration is inversely proportional to the flutter frequency and flutter velocity. The impact of centroid offset on blade structure flutter frequency is minimal, but the centroid offset in the tip region has a greater impact on flutter velocity. Increasing the torsional frequency can prevent coupled mode flutter and provide a theoretical basis for blade flutter prevention design.

Prediction of ultimate tensions in mooring lines for a floating offshore wind turbine considering extreme gusts

The design of mooring line parameter for a floating offshore wind turbine (FOWT) should consider the ultimate limit state. Typhoons should be considered as a threatening condition for mooring design, and the characteristics of transient changing wind should be studied. Currently, few extreme value predictions consider gust features, and extreme mooring tensions may be underestimated in practical FOWT design. We conducted the simulations of the 5 MW wind turbine from the National Renewable Energy Laboratory (NREL) in the environmental conditions of extreme gusts, waves, and currents. Extreme gusts were found to cause dramatic increases in mooring tensions under 100-year typhoon conditions. The average conditional exceedance rate (ACER) method is used to predict extreme mooring tensions. The impacts of simulation duration and sample size on the prediction results are then discussed. The results show that in extreme gust conditions, the tail data of the average conditional exceedance rate of mooring tension presents a different extrapolation trend from stable wind conditions. Short-term predicted values in gust conditions are 14–20% larger than those in stable wind conditions. The research shows the necessity of considering threatening gust conditions in the ultimate limit state design of mooring system of FOWT.

Aeroacoustic source localization using the microphone array method with application to wind turbine noise

The deconvolution DAMAS algorithm can effectively eliminate the misconceptions in the usually-used beamforming localization algorithm, allowing for a more accurate calculation of the source location as well as the intensity. When solving a linear system of equations, the DAMAS algorithm takes into account the mutual influence of different locations, reducing or even eliminating sidelobes and producing more accurate results. This work first introduces the principles of the DAMAS algorithm. Then it applies both the conventional beamforming algorithm and the DAMAS algorithm to simulate the localization of a single-frequency source from a 1.5 MW wind turbine, a complex line source with the text “UCAS” and a line source downstream of an airfoil trailing edge. Finally, the work presents experimental localization results of the source of a 1.5 MW wind turbine using both the conventional beamforming algorithm and the DAMAS algorithm.

Impact of motions on floating wind turbine power production

Floating offshore wind opens new possibilities for harnessing wind energy in deeper waters where it is not feasible to install traditional fixed-bottom turbines. Accessing deeper waters enables the utilization of stronger and more consistent wind resources, potentially leading to higher energy production. However, one of the challenges of floating offshore wind is the impact of increased motions on floating turbine’s power. This paper addresses this challenge by investigating wind field reconstruction and motion compensation algorithms when using a nacelle lidar to characterize floating turbine inflow wind speed. The fully instrumented TetraSpar floating demonstrator with a 3.6 MW wind turbine and a nacelle lidar, offers a unique opportunity to investigate the effect of motions on power production. Observations from real measurements are complemented with numerical simulations, highlighting that motion-compensating for mean tilt angle is an effective correction for 10 min average power performance measurements. Results showed that mean tilt angles causing the lidar beams to shift upwards, result in overestimation of the estimated hub height wind speed if no motion compensation is applied. The paper also assesses the impact of motions induced by different sea states on power production.

Wind turbine main shaft crack detection with SCADA generator speed measurement

Preventing failure of structural components is a necessity for safe and economic operation of wind farms. This paper presents a novel detection method of wind turbine main shaft fractures based on data from the turbine SCADA system thus not needing retrofit sensors. The authors developed the crack detection method in the wake of a catastrophic failure on an offshore 3.6 MW wind turbine and applied it across multiple wind farms totalling more than a thousand turbines of the same type, minimising any further risk of failure. The novel method consists of tracking the amplitude of the 2P rotor harmonic in the generator speed and is found to outperform the most common metrics proposed in shaft crack detection literature: Rotor harmonics measured in fore-aft and side-side accelerations and estimates of the drivetrain torsional eigenfrequencies. The generator speed 2P amplitude of the cracked shaft turbine was significantly elevated 16 months before failure while all other benchmark metrics failed to detect the crack. The analysis showed that no other turbine in the fleet were exhibiting similar indications of main shaft cracks and indicated that any such failure would have a long lead time.

Validating low- and high-fidelity simulations of a yawed 8 MW wind turbine against measurements

This paper presents a comparison study of the aerodynamic behavior of an 8 MW wind turbine operating under yawed conditions using field measurements, Blade Element Momentum (BEM) theory and Computational Fluid Dynamics (CFD). Turbulent inflow wind field measurements are used to generate an IEC-compliant turbulence box upstream of the wind turbine that is used within the BEM tool MoWiT and the CFD tool chain by IWES in OpenFOAM. Both simulation approaches take into account blade flexibility using modal reduced, anisotropic beam elements in BEM and Geometrically Exact Beam Therory (GEBT) in CFD. While the focus is being set towards the CFD approach, turbine power output, blade root bending moments and blade tip deflections are analyzed. It is shown that both modeling approaches react differently towards the generated wind field.

Computational investigation of the effect of the trailing edge thickness on the wind turbine performance

Trailing edge (TE) thickness is a manufacturing constraint in blade design, especially for airfoils with a sharp TE. To achieve a specific TE thickness, blade geometry is often modified during the design process, typically in the outer zone of the blade where the airfoil’s TE is thinner. This area has a significant impact on energy production and loads. Quantifying the effect of TE thickness modifications is crucial for making informed design decisions.Therefore, this study quantifies and compares the impact of linear and polynomial geometry modifications on airfoil aerodynamics and turbine performance. Xfoil and OpenFAST were used to calculate these performance variations in the well-known NREL 5 MW wind turbine. The TE thickness of the model was modified to meet various manufacturing constraints, ranging from no restriction to a limit of 12mm TE thickness.In terms of the aerodynamic behavior of the airfoils, the maximum efficiency of airfoils with low relative thickness decreases as the TE thickness increases. Annual Energy Production shows a reduction of up to 0.42% for the worst case, while blade root loads increase by up to 20%. For low relative thickness airfoils, the linear method has proven to be a better option with less impact on performance.

A directivity correction for accurate semi-empirical wind turbine noise prediction

Public acceptance of wind farms is a significant challenge in the development of wind energy. The acoustic impact generated by wind turbines is a common concern among local residents. The primary noise source in wind turbines is generated by aerodynamics. Atmospheric turbulence reaching the blade leading edge or turbulent boundary layer passing the trailing edge produce the main aeroacoustic sources. The noise generated by these mechanisms is commonly predicted by means of semi-empirical models, which do not demonstrate great reliability when compared to acoustic measurements. This paper presents a correction to the directivity of airfoil noise radiation, resulting in improved sound pressure levels on the ground plane surrounding a wind turbine. This improvement is achieved without requiring any additional computational effort. The sound pressure levels perceived on the ground plane are known to have asymmetrical shape. Maximum noise levels correspond to observers directly in the upwind and downwind locations, whereas the minimum levels belong to the positions close to the rotor plane. Said asymmetrical shape is not represented in the semi-empirical models. The proposed correction takes into consideration the airfoil thickness in the radiation directivity equations, resulting in the expected asymmetrical shape of noise footprints on the ground plane around a wind turbine. The correction was found to not affect the accuracy of the spectrum predicted by the semi-empirical models when compared to dedicated field measurements under the standard IEC 61400-11 procedure. When implementing the proposed correction, the virtual NREL 5 MW wind turbine’s published noise footprints, which were originally calculated using computationally expensive methods, are accurately reproduced.