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During their service life, monopiles supporting offshore wind turbines are subjected to a large number of lateral cyclic loads resulting from complex environmental conditions such as wind and waves varying in amplitude, direction, load eccentricity and frequency. The consequential accumulation of displacements and rotations of the foundation structure with cyclic loading is one key concern in the design of monopiles. Nevertheless, the relevant offshore guidelines do not provide suitable procedures for predicting such deformations. Although there are several methods for this purpose in the literature, some of them produce very different or even contradictory results, which prevents a consistent approach to dimensioning. This paper briefly summarizes the current standardization regarding design of monopiles for cyclic lateral loading and provides some examples of possible prediction models from the literature. To highlight the need for further research, the predictions according to different approaches are compared and evaluated by a calculation example and a parameter study. Further, the results of a small-scale 1 g model test campaign on the load-displacement behaviour of monopile foundations subjected to lateral cyclic loading and the influencing parameters are presented, evaluated and compared with the findings of other research groups. In this way the test results can help to support or improve model development and provide insight into key issues relevant to monopile design. The parameters that have been assessed include the cyclic load magnitude, cyclic load ratio, load eccentricity, soil relative density, the grain size distribution of the non-cohesive bedding material and the pile embedment length. [ABSTRACT FROM AUTHOR]

In this study, the seismic soil-structure interaction (SSI) of wind turbine support structures is investigated based on the complex mode superposition approach. For accurate and efficient estimation of seismic loadings on wind turbine support structures, an augmented complex mode superposition response spectrum method (RSM) is developed, where the maximum shear force and bending moment of the non-classically damped system are analytically derived. An empirical formula of the modal damping ratios with a threshold value for the allowable damping ratio is also proposed to improve the prediction accuracy of the shear force acting on the footing. Furthermore, additional loadings to consider the contribution of the mass moment of inertia of rotor and nacelle assembly and P 1 effect to the bending moment on the tower are analytically derived. The proposed formulae are first demonstrated upon a 2MW wind turbine supported by two different types of foundations. A parametric study is then carried out by changing the tower geometries and soil conditions to propose the threshold value for the allowable damping ratio. [ABSTRACT FROM AUTHOR]

This paper describes the design and characterization of a scaled wind turbine model, conceived to support wake and wind farm control experiments in a boundary layer wind tunnel. The turbine has a rotor diameter of 0.6m and was designed to match the circulation distribution of a target conceptual full-scale turbine at its design tip speed ratio. In order to enable the testing of plant-level control strategies, the model is equipped with pitch, torque and yaw actuation and is sensorized with integrated load cells, rotor azimuth and blade pitch encoders. After describing the design of the turbine, its steady-state performance and wake characteristics are assessed by conducting experiments in two different wind tunnels, in laminar and turbulent conditions, collecting wake data with different measurement techniques. A large-eddy simulator coupled to an actuator-line model is used to develop a digital replica of the turbine and of the wind tunnel. For increased accuracy, the polars of the low-Reynolds-number airfoil used in the numerical model are tuned directly from measurements obtained from the rotor in operation in the wind tunnel. Results indicate that the scaled turbine performs as expected: measurements are repeatable and consistent, and the wake appears to have a realistic behavior in line with expectations and with a similar but slightly larger scaled model turbine. Furthermore, the predictions of the numerical model are well in line with experimental observations. [ABSTRACT FROM AUTHOR]

Annual energy production (AEP) is often the objective function in wind plant layout optimization studies. The conventional method to compute AEP for a wind farm is to first evaluate power production for each discrete wind direction and speed using either computational fluid dynamics simulations or engineering wake models. The AEP is then calculated by weighted-averaging (based on the wind rose at the wind farm site) the power produced across all wind directions and speeds. We propose a novel formulation for time-averaged wake velocity that incorporates an analytical integral of a wake deficit model across every wind direction. This approach computes the average flow field more efficiently, and layout optimization is an obvious application to exploit this benefit. The clear advantage of this new approach is that the layout optimization produces solutions with comparable AEP performance yet is completed 2 orders of magnitude faster. The analytical integral and the use of a Fourier expansion to express the wind speed and wind direction frequency create a relatively smooth solution space for the gradient-based optimizer to excel in comparison to the existing weighted-averaging power calculation. [ABSTRACT FROM AUTHOR]

Over the past decades, Floating Offshore Wind Turbine (FOWT) has gained increasing attention in wind engineering due to the rapidly growing energy demands. However, difficulties in turbine maintenance will increase due to the harsh operational conditions. Fault diagnosis techniques play a crucial role to enhance the reliability of FOWTs and reduce the cost of offshore wind energy. In this paper, a novel data‐driven fault diagnosis method using regularized dynamic canonical correlation analysis (RDCCA) and Fisher discriminant analysis (FDA) is proposed for FOWTs. Specifically, to overcome the collinearity problem that exists in measured process data, dynamic canonical correlation analysis with a regularization scheme, is developed to exploit the relationship between input and output signals. Then, the residual signals are generated from the established RDCCA model for fault detection. To further classify the fault type, an FDA model is trained from the residual signals of different training faulty data sets. Simulations on a FOWT baseline model based on the widely used National Renewable Energy Laboratory FAST simulator are carried out to demonstrate the feasibility and efficacy of the proposed fault detection and classification method. Results have shown many salient features of the proposed method with potential applications in FOWTs. [ABSTRACT FROM AUTHOR]

This study presents a new turbine layout optimisation approach using a grid‐based problem formulation for improved design performance and computational efficiency for industrial‐scale applications. A particle swarm optimisation algorithm is employed in the wind turbine layout optimisation, in which a micro‐siting function is proposed to allow solutions 50 m of deviation while maximising energy capture without compromising maritime navigation or search and rescue operations. Solutions are assessed by a wind farm model, comprising the Larsen wake model, a multiple wake effect summation method, and a rotor‐effective wind speed calculation. A novel look‐up function is populated by on‐the‐fly algorithm and is used to reduce the number of model evaluations by approximately 95%. A gigawatt scale hypothetical site is presented to test the model on a realistically complex scenario. A set of design solutions generated by the algorithm are compared to empirical designs, with the algorithm outperforming the empirical solutions by 7.55% on average, in terms of net‐present‐value of energy capture minus the capital cost of turbines. The numerical efficiency and design effectiveness are examined and further improvements discussed. [ABSTRACT FROM AUTHOR]

In order to carry out a precise and high-reliability design for the main shaft of MW wind turbine, a strength analysis and optimiza tion method was proposed based on WorkBench. Firstly, The finite element model of main shaft with accessories was established, a lamina model was used to simulate bearing, and the ultimate strength and fatigue strength of the main shaft were calculated according to IEC standard. Then the relevant design variables were defined and parameterized according to the hot spot's location, and the response surfaces model were built and analyzed by using the DOE method of LHS. To minimize the weight and equivalent stress, a multi-objective optimization algorithm was used to optimize and the results were verified. The results show that the mass of main shaft is reduced by 2% after optimization, the maximum stress is reduced by 8%, and the safety margin of fatigue increased by 16.56%. The reliability and economy of main shaft have been improved. [ABSTRACT FROM AUTHOR]

Wind turbine wake models typically require approximations, such as wake superposition and deflection models, to accurately describe wake physics. However, capturing the phenomena of interest, such as the curled wake and interaction of multiple wakes, in wind power plant flows comes with an increased computational cost. To address this, we propose a new hybrid method that uses analytical solutions with an approximate form of the Reynolds-averaged Navier-Stokes equations to solve the time-averaged flow over a wind plant. We compare results from the solver to supervisory control and data acquisition data from the Lillgrund wind plant obtaining wake model predictions which are generally within 1 standard deviation of the mean power data. We perform simulations of flow over the Columbia River Gorge to demonstrate the capabilities of the model in complex terrain. We also apply the solver to a case with wake steering, which agreed well with large-eddy simulations. This new solver reduces the time - and therefore the related cost - it takes to simulate a steady-state wind plant flow (on the order of seconds using one core). Because the model is computationally efficient, it can also be used for different applications including wake steering for wind power plants and layout optimization. [ABSTRACT FROM AUTHOR]

The rapid development of the wind industry in recent decades and the establishment of this technology as a mature and cost-competitive alternative have stressed the need for sophisticated maintenance and monitoring methods. Structural health monitoring has risen as a diagnosis strategy to detect damage or failures in wind turbine structures with the help of measuring sensors. The amount of data recorded by the structural health monitoring system can potentially be used to obtain knowledge about the condition and remaining lifetime of wind turbines. Machine learning techniques provide the opportunity to extract this information, thereby improving the reliability and cost-effectiveness of the wind industry as well. This paper demonstrates the modelling of damage-equivalent loads of the fore-aft bending moments of a wind turbine tower, highlighting the advantage of using the neighbourhood component analysis. This feature selection technique is compared to common dimension reduction/feature selection techniques such as correlation analysis, stepwise regression, or principal component analysis. For this study, recordings of data were gathered during approximately 11 months, preprocessed, and filtered by different operational modes, namely standstill, partial load, and full load. The results indicate that all feature selection techniques were able to maintain high accuracy when trained with artificial neural networks. The neighbourhood component analysis yields the lowest number of features required while maintaining the interpretability with an absolute mean squared error of around 0.07% for full load. Finally, the applicability of the resulting model for predicting loads in the wind turbine is tested by reducing the amount of data used for training by 50 %. This analysis shows that the predictive model can be used for continuous monitoring of loads in the tower of the wind turbine. [ABSTRACT FROM AUTHOR]

This paper describes the design and testing of an axial induction controller implemented on a row of nine turbines on the Sedini wind farm in Sardinia, Italy. This work was performed as part of the EU Horizon 2020 research project CL-Windcon. An engineering wake model, selected for its good fit to historical SCADA data from the site, was used in the LongSim code to optimise turbine power reduction setpoints for a large matrix of steady-state wind conditions. The setpoints were incorporated into a dynamic control algorithm capable of running on-site using available wind condition estimates from the turbines. The complete algorithm was tested in dynamic time-domain simulations using LongSim, using a time-varying wind field generated from historical met mast data from the site. The control algorithm was implemented on-site, with the wind farm controller toggled on and off at 35 min intervals to allow the performance with and without the controller to be compared in comparable wind conditions. Data were collected between July 2019 and early February 2020. The results have been analysed and indicate a positive increase in energy production resulting from the induction control, in line with LongSim model predictions, although a larger volume of valid data would be necessary to provide statistically robust conclusions. The measurements also provide a validation of the LongSim model, proving its value for both steady-state setpoint optimisation and time-domain simulation of wind farm performance. [ABSTRACT FROM AUTHOR]

The energy produced by wind plants can be increased by mitigating the negative effects of turbine-wake interactions. In this context, axial-induction control and wake redirection control, obtained by intentionally yawing or tilting the rotor axis away from the mean wind direction, have been the subject of extensive research but only very few investigations have considered their combined effect. In this study we compute power gains that are obtained by operating tilted and yawed rotors at higher axial induction by means of large-eddy simulations using the realistic native National Renewable Energy Laboratory (NREL) 5MW actuator disk model implemented in the Simulator for On/Offshore Wind Farm Applications (SOWFA). We show that, for the considered two-row wind-aligned array of wind turbines, the power gains of approximately 5% obtained by standard wake redirection at optimal tilt or yaw angles and reference axial induction can be more than tripled, to above 15 %, by operating the tilted or yawed turbines at higher axial induction. It is also shown that significant enhancements in the power gains are obtained even for moderate overinduction. These findings confirm the potential of overinductive wake redirection highlighted by previous investigations based on more simplified turbine models that neglected wake rotation effects. The results also complement previous research on dynamic overinductive yaw control by showing that it leads to large power gain enhancements also in the case where both the yaw and the overinduction controls are static, hopefully easing the rapid testing and implementation of this combined-control approach. [ABSTRACT FROM AUTHOR]

The modelling of each horizontal axis wind turbine (HAWT) differs due to variation in operating conditions, dynamic parameters, and components. Thus, the choice of profiles also varies for specific applications. So for the better choice of profiles, the wind turbine performance is analysed for different parameters and working conditions. The efficiency of HAWTs mainly depends on the blade, which in turn is related to the profile of the blade, blade orientation, and tip size. Hence, the main aim of the present work is to evaluate the performance of HAWTs for three different blade tip sizes and six different blade twist angles for three major NACA (National Advisory Committee for Aeronautics) airfoils. A statistical analysis is also carried out to find the influence of different performance parameters such as drag, lift, vorticity, and normal force. The static design parameters are considered based on the available literature. A three-bladed offshore HAWT is adopted as the research object in the study. Data visualization using star glyphs and sunray plots is performed, along with multilinear regression analysis. From the multilinear regression analysis and reliable empirical correlations, it is known that drag coefficient and lift coefficient parameters have less significance in contrast to the other parameters which have more significance in the regression model. The different results obtained in terms of parametric coefficients provide an effective way to generate appropriate airfoil profiles for given HAWTs. Thus, the study helps to achieve better turbine performance, and it serves as a benchmark for future studies on HAWTs. [ABSTRACT FROM AUTHOR]

The article provides information on the higher energy generation with francis turbines including consequences of climate change with a frequency converters, energy production at reduced water supply and gearbox connection. Topics include synchronous generators, hydropower plants and speed of the turbine as well an increase in performance.

In this article, a new pitch control scheme is proposed for three‐bladed wind turbines to reduce two types of ripples caused by wind shear and tower shadow, including 1P aerodynamic loads and multiples of 3P torque ripples. These ripples are mathematically proven to be associated with wind power by using an equivalent wind speed model. An individual pitch control strategy is then proposed to reduce the impacts of the two types of ripples on wind turbines. In the proposed pitch control strategy, two band‐pass filters are implemented to obtain the ripple components, and a supplementary pitch angle reference signal is generated for each wind blade based on the ripple components and rotor azimuth. By adding the supplementary pitch angle adjustment signal to the existing pitch angle reference, a new pitch angle reference signal is produced to reduce 1P aerodynamic loads and multiples of 3P torque ripples. Several tests show that the proposed pitch control strategy has a good performance to alleviate the 1P aerodynamic load ripples and multiples of 3P torque ripples. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this article a wind turbine performance enhancement is studied numerically using two type of tip plates. A three dimensional finite volume code is developed to simulate the wind turbine flow field periodically at different wind speeds and pitch angles. The well-known Menter's Shear Stress Transport (k ω − S S T) turbulence modelling is incorporated into the code to investigate the turbulent flow field that occurs in wind turbines. Here we show that using tip plates for wind turbines performance improvement can only occur if the turbine blade pitch angle is set at the maximum output power based on the given wind speed. Otherwise, using the tip plates play negative role and reduce the wind turbine output power. This physical effect is related to the wind turbine working condition at which both the blade span-wise flow as well as the tip blade trailing vortices stay at their minimum amount. • Highlight: • Detailed study of the effect of adding tip plate to the wind turbine blade on the wind turbine performance. • Pointing out the span-wise flow importance on the wind turbine performance. • Exploring the range of pitch angles and wind speeds at which adding tip plates can improve the wind turbine performance. [ABSTRACT FROM AUTHOR]

The power curve of a wind turbine describes the generated power versus instantaneous wind speed. Assessing wind turbine performance under laboratory ideal conditions will always tend to be optimistic and rarely reflects how the turbine actually behaves in a real situation. Occasionally, some aerogenerators produce significantly different from nominal power curve, causing economic losses to the promoters of the investment. Our research aims to model actual wind turbine power curve and its variation from nominal power curve. The study was carried out in three different phases starting from wind speed and related power production data of a Senvion MM92 aero-generator with a rated power of 2.05 MW. The first phase was focused on statistical analyses, using the most common and reliable probability density functions. The second phase was focused on the analysis and modelling of real power curves obtained on site during one year of operation by fitting processes on real production data. The third was focused on the development of a model based on the use of an Artificial Neural Networks that can predict the amount of delivered power. The actual power curve modelled with a multi-layered neural network was compared with nominal characteristics and the performances assessed by the turbine SCADA. For the studied device, deviations are below 1% for the producibility and below 0.5% for the actual power curves obtained with both methods. The model can be used for any wind turbine to verify real performances and to check fault conditions helping operators in understanding normal and abnormal behaviour. • A neural network model of wind turbine power curve is developed from real data. • Accurate statistical analyses are carried out on wind and weather data. • Neural network model is based on several, often neglected, parameters. • Results demonstrate effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Flow characteristics over a dynamic section of wind turbine blade in the presence of super-hydrophobic coatings were studied numerically using computational fluid dynamics method. Assuming a super-hydrophobic coating, blade icing can potentially be prevented. Fluids on super-hydrophobic surfaces are moving; so slip velocity exists on their walls. The dynamic motion was in sinusoidal mode that caused deep dynamic stall (DS) phenomenon. The occurrence of DS results in enlarged vortices with high strength of vorticity. These vortices cause overshoot in aerodynamic loads. By applying a super-hydrophobic surface on different locations of the airfoil, the DS vortex generation can be definitely affected. Investigation of these effects, is the aim of this paper. There is no study in the literature that analyzed DS in the presence of slip velocities at different locations. Thus, an SD7037 airfoil was simulated at R e ≈ 4 × 10 4 using Transition-SST model. Results demonstrated that as the coating covered the leading edge, DS and vortex formation were postponed and the lift peak reduced about 10.6%; while for airfoil entirely covered by coating, the maximum lift value was augmented 14.6% and DS delayed. Applying slip boundary conditions at trailing edge as well as the pressure side had not considerable changes in cyclic loads. • In cold climates, wind turbine blades may be iced; blade icing can dramatically reduce performance. • A water-repellant surface can potentially prevent atmospheric icing on the blades. • Dynamic stall is a limiting phenomenon for designing horizontal axis wind turbines. • Turbine blade performance in the presence of super-hydrophobic surfaces during dynamic stall occurrence analyzed. • The location of coating had different results for cyclic loads. At the pressure side, no noticable effects were observed. [ABSTRACT FROM AUTHOR]

Abstract The aerodynamic performance of wind turbine rotor blades is influenced by the leading edge condition. Contamination and erosion cause increased surface roughness, unevenness or defects, which affect the boundary layer flow and, thus, reduce lift and increase drag. Current approaches used to determine the disturbed boundary layer flow are based on invasive flow probes with limited spatial resolution; therefore, a non-invasive, camera-based measurement of the boundary layer flow disturbances on wind turbines in operation is proposed using thermographic flow visualization. The actual and the undisturbed laminar-turbulent transition positions are determined in the thermographic images and a subsequent assignment to the rotor blade geometry obtains chord-based information. The normalized difference of both transition positions can be used as a metric to describe the extent of the disturbed boundary layer flow. The approach is demonstrated on a multi-MW horizontal axis wind turbine with a laminar flow reduction of up to 90.4 %. Furthermore, the measurement results allow the estimation of the annual energy production loss due to the leading edge condition, which enhances the industrial standard of simply comparing clean and tripped aerodynamic polars. For the investigated wind turbine, the annual energy production loss amounts to 4.7 % at 6 m/s average wind speed. Highlights • Thermographic measurements enable a characterization of the leading edge condition. • The measurement method proposed is non-invasive and can be used while operation. • The annual energy production loss due to erosion and contamination is estimated. • The estimation is based on the actual thermographic field measurement data. [ABSTRACT FROM AUTHOR]

Abstract Renewable energy systems are promoted and developed notably due to their low environmental footprint. Fleet-wide robust environmental assessments are needed to drive the sustainable transition of energy systems worldwide. This study introduces a tailored comprehensive impact assessment methodology for fleets of renewable energy systems based on Life Cycle Analysis and its application to Danish wind turbines fleet through an online platform LCA_WIND_DK (viewer.webservice-energy.org/lca-wind-dk/). This platform enables to visualize environmental performances of wind turbines in Denmark and their temporal evolution. The fleet is known in detail from 1980 to 2016 and projected from 2017 to 2030 based on national objectives for onshore/offshore capacity and pre-approved offshore projects. Each turbine's future electricity production is estimated from its power curve and geo-localized wind time-series. More than 10,000 cradle-to-grave life cycle inventories are generated, considering the spatio-temporal context and technological characteristics. The comprehensive analysis of the Danish fleet over fifty years reveals long-term trends for several impact categories. Improvements in all categories follow similar trends as in climate change, which decreases from 40 to 13 g CO2-eq/kWh between 1980 and 2030. Improvements stem from combined economies of scale and higher load factors linked to increasingly large and powerful turbines. The interactive mapping tool LCA_WIND_DK may provide statistics to support renewable energy oriented policy scenarios and unique spatio-temporal environmental information to project developers. This novel approach designed for large territories, here applied to the Danish wind turbine fleet, is generic and can be applied to other renewable energy systems and/or to other territories. Highlights • a generic impact assessment methodology for renewable energy fleets. • Wind power projections from national targets, GIS wind data and power curve modeling. • a fleet-wide robust environmental assessment of the wind turbines in Denmark. • LCA_WIND_DK: a Web platform to visualize environmental performances of wind turbines. • Improvement of the carbon footprint: from 40 to 13 g CO 2 -eq/kWh between 1980 and 2030. [ABSTRACT FROM AUTHOR]

Vertical Axis Wind Turbines (VAWTs) are suitable for use in populated areas. The main parameter of the design of this type of the wind turbine is the cross sectional profile of the turbine blade. Additionally, the turbine performance and the generated aerodynamic noise of the VAWTs are critical issues that could limit the spreading of these turbines especially in the residential zones. In the last years, some publications investigated the J-shape Darrieus turbine and praised the performance of this design. Therefore, the present investigation introduces a criticism of the J-shape Darrieus Vertical Axis Wind Turbine (J-SD-VAWT) with three-bladed rotor. An accurate comparison has been introduced for three different turbines with different airfoils sections (NACA 0015, NACA 0021 and S1046). The comparison included the standard airfoil design and the J-shape of the same airfoils from two points of views of turbine performance and noise generation. Aero-acoustics and performance of the proposed design was thoroughly investigated using the Computational Fluid Dynamics (CFD). Both the Unsteady Reynolds-averaged Navier-Stokes (URANS) equations and the impermeable Ffowcs Williams and Hawkings (FW-H) equation were simultaneously solved. The effects of J-shape cut ratio, speed ratio, and turbine solidity were investigated. For all configurations, the results indicated that J-shape reduced the performance and did not reduce the turbine noise. • The present study considers J-shape Darrieus wind turbine. • Effect of different J-shape airfoils on the turbine performance is investigated. • J-shape airfoils noise is evaluated and compared with standard turbine. • J-shape design is not recommended for Darrieus wind turbine. [ABSTRACT FROM AUTHOR]

Vertical axis wind turbines present several advantages over the horizontal axis machines that make them suitable to a variety of wind conditions. However, due to the complexity of vertical axis wind turbine (VAWT) aerodynamics, available literature on VAWT performance in steady and turbulent wind conditions is limited. This paper aims to numerically predict the performance of a 5 kW VAWT under steady wind conditions through computational fluid dynamics modeling by varying turbine configuration parameters. Two-dimensional VAWT models using a cambered blade (1.5%) were created with open field boundary extents. Turbine configuration parameters studied include blade mounting position, blade fixing angle, and rotor solidity. Baseline case with peak Cp of 0.31 at tip-speed ratio of 4 has the following parameters: mounting position at 0.5c, zero fixing angle, and three blades (solidity = 0.3). Independent parametric studies were carried out and results show that a blade mounting position of 0.7c from the leading edge produces the best performance with maximum Cp = 0.315 while the worst case is a mounting position of 0.15c with peak Cp = 0.273. Fixing angle study reveals a toe-out setting of −1° producing the best performance with peak Cp of 0.315 and the worst setting at toe-in of 1.5° with peak Cp of 0.287. The solidity study resulted in the best case of four blades (solidity = 0.4) with peak Cp = 0.316 and the worst case of two blades (solidity = 0.2) with peak Cp = 0.283. [ABSTRACT FROM AUTHOR]

Vertical-axis wind turbines (VAWTs), which are considered an important wind energy conversion device, have recently received renewed attention. Researchers are investigating the pitch angle control method to improve the wind energy utilization efficiency of VAWTs. In this study, ANSYS Fluent is used to investigate the aerodynamic performance of two-dimensional VAWTs. Different pitch angles are investigated using unsteady Reynolds-averaged Navier–Stokes calculations, and turbulence is modeled with the shear stress transport k–ω model. Four quartiles are defined for the azimuthal angle of a rotation period: upwind (45 ° < θ < 135 °), leeward (135 ° < θ < 225 °), downwind (225 ° < θ < 315 °), and windward (315 ° < θ < 45 °). Furthermore, the sliding-mesh technique and a user-defined function are applied to adjust the pitch angle of the wind turbine blades in different azimuthal zones. This study proposes a pitch angle control method that effectively improves the efficiency of VAWTs by comprehensively analyzing the aerodynamic performance of the wind turbine and power coefficient (C p) variation in each zone. The results indicate that an appropriate pitch angle control solution can significantly improve the efficiency of the wind turbine. Compared to a fixed pitch angle of 0°, an approximately 17.0% increase in C p can be achieved and, compared to the optimal fixed pitch angle −1°, an approximately 12.0% increase in C p can be achieved. • Pitch angles of −5° to +4° and the effect on the VAWT power are investigated. • Obtain the optimal pitch angle for each quartile to optimize blade pitch control. • Suitable pitch angle control solution increases the turbine C p by 12.0% compared to ADNI. [ABSTRACT FROM AUTHOR]

Abstract A sound maintenance policy of wind turbine occupies an important position in reducing the operations and maintenance (O&M) costs. However, few papers consider system performance, e.g. system availability, reliability, mean time to failure, into the maintenance policy. A novel optimal maintenance policy based on the performance-based contract (PBC) is presented to maximize the profit of suppliers meanwhile improving the system availability. Here, three maintenance actions are adopted: opportunistic maintenance, preventive maintenance and corrective maintenance. In precious researches where the objective was to minimize the O&M costs or maximize the system availability, while in this paper the maximum profit was used. To compare the proposed policy with conventional policies, three criterions are presented: maximum profit, greenhouse gas emissions and system availability. Finally, an illustrative numerical example is provided to demonstrate the applicability and superiority of the proposed model. Highlights • A novel maintenance policy based on performance-based contract is proposed. • Opportunistic maintenance policy is used to share the set-up cost and reduce the maintenance cost. • Different components in wind turbine are simultaneously studied and economic dependencies are considered among them. [ABSTRACT FROM AUTHOR]

Fault detection in wind turbine which is identified with complete system monitoring under multi-fault scenario is proposed. When a fault is detected, its types and location are recognized for easy maintenance. Fault in wind turbines is caused due to the high speed of gearbox, generator bearing and the failures occurred in various parts. In wind farm, wind turbine condition monitoring is used to reduce the maintenance cost and also improves the accuracy. Generally, in wind turbine gearbox condition monitoring using sensor is a gainful method to monitor wind turbine performance and fault. This paper nominates a method to decide the parameters for support vector machine (SVM) in wind turbine called Cuckoo search optimization (CSO). The combination of optimization technique with classification technique is evaluated. MATLAB platform was used to evaluate the various faults under fixed value and gain factor conditions. Comparing the accuracy with SVM, particle swarm optimized SVM and k-nearest neighbor, the proposed fault detection and fault isolation technique (CSO-SVM) is improved by 2.5%, 3.5% and 6.5%, respectively. The result shows the CSO model based on SVM algorithm accomplishes the most accurate fault detection than the past models. [ABSTRACT FROM AUTHOR]

In this study, the performance of a ducted wind turbine is compared with a bare one using wind tunnel results. Ducted turbines are a type of small wind turbines, which consist of a diffuser surrounding the rotor. The duct makes more air flow in rotor plain and as a result augments power production. The blade was fabricated, using resin polyester armed by glass fiber. Duct is formed by sheet metal rolling in slope to have an acceptable appearance. According to BEM design, predicted power for the bare turbine is 300W in wind velocity 10 m/s considering 20% loss due to bearing resistant, rotor inertia, and generator efficiency. Wind tunnel investigation revealed 165W power experimentally for bare wind turbine. The evaluation of the system in the wind tunnel showed that the power augmentation of the ducted system compared to the bare one was 37% higher on average. The maximum power augmentation of the ducted turbine was 286W. The rotor speed of ducted turbine was 61% more than the bare turbine, which increased the speed of the tip of the blade. [ABSTRACT FROM AUTHOR]

Abstract The capacity of installed wind power is growing rapidly in cold climate regions; however, turbine blades are susceptible to ice accumulation. The aerodynamic properties of turbine blades are highly sensitive to ice accretion, which can significantly impair aerodynamic performance. Ice accretion on the blades of a wind turbine can lead to turbine shutdown, power loss and damage to turbine components. To prevent ice formation on wind turbine blades, an ice sensor integrated with an ice mitigation system is required. The ice sensor can be used with a de-icer on the blade surface. However, the current ice sensing and de-icing technologies are inefficient and integrated systems need appreciable improvement. This paper reviews ice sensing and active mitigation techniques for a wind turbine blade surface, which are categorized based on several key parameters. Furthermore, this paper investigates the conceptual design of integrating ice sensing and mitigation systems. The advantages and disadvantages of the integrated systems are presented to provide valuable insights on ice prevention for wind turbines operating in ice prone locations. Highlights • Ice sensing and active mitigation techniques for a wind turbine blade surface. • Review of conceptual designs of integrating ice sensing and mitigation. • Thorough review of advantages and disadvantages of integrated systems. [ABSTRACT FROM AUTHOR]

Highlights • Grid thickness plays serious role in the actuator disk model of wind turbine rotor. • The classic actuator disk model users considered constant grid thickness values. • Actuator disk model solution is accurate if optimum grid thickness value is chosen. • This work improves actuator disk model by imposing real blade thickness values. • The improved actuator disk model yields result as accurate as that of optimum one. Abstract Actuator disc models are frequently used to provide a semi-analytical approach to estimating aerodynamic loads on rotary blades. The basic idea is to distribute the aerodynamic loads on a virtual rotating disc instead of simulating the actual rotating blade. These loads are then imposed to represent the source terms of the Navier-Stokes equations, which can be solved numerically using the computational fluid dynamic methods. The thickness of the actuator disk grid is one important factor considerably affecting calculations of the wind turbine rotor. Past researches generally considered the idea of fixed grid thickness exerting along the blade in their actuator disk modeling. However, this study introduces an innovative or improved actuator disk model, which takes into account the real blade thickness of a wind turbine in the computational fluid dynamic simulations. This novel actuator disk model is then incorporated into a finite-volume solver. This solver uses the second-order central and upwind schemes to approximate the diffusive and advective fluxes at the cell faces, respectively. The k-ε turbulence model is used to close the turbulence closure problem. The NREL 5-MW wind turbine blade is chosen as a benchmark test to evaluate the results of the newly developed solver for the numerical predictions of the wind turbine rotor. The current study reveals that there is a specific fixed grid thickness value resulting in the most accurate predictions though with a much slower convergence rate. This specific value really depends on the chosen test cases and varies from one case to another. Its exact value may be found via try-and-error procedures, which would be computationally very expensive and time-consuming. Alternatively, this study introduces an improved actuator disk model capable of reinstating the real blade thickness in calculations. Subsequently, the wind turbine rotor performance is predicted numerically using both the improved and classic actuator disk models applying various fixed grid thickness values along the blade. The results demonstrate that the accuracy of the classic actuator disk model strongly depends on the grid thickness magnitude. On the contrary, the newly improved actuator disk model results in some solutions, which are as accurate as those of the most accurate classic actuator disk model, while suitably speeding up the convergence rate. [ABSTRACT FROM AUTHOR]

Summary: Wind turbine (WT) power curves effectively reflect the generation performance of WTs and depict the relationship between the wind speed and the WT power output. This paper aims at developing an effective method for learning the intrinsic representations of WT power curves, which are robust to external environmental changes. Based on the obtained representations, WT generation performance is monitored. In the proposed approach, data of the supervisory control and data acquisition (SCADA) system is employed to derive the representations. Parametric models of WT power curves are developed using the two‐parameter and four‐parameter logic models. The parameters of these model are identified via Jaya algorithm. To detect the changes of WT power curve model parameters over different time, multivariate control charts are employed. The effectiveness of the proposed WT generation performance monitoring approach is validated based on SCADA data collected from real commercial WTs. Jaya algorithm is applied to estimate parameters of the parametric power curve model.The multivariate control chart is employed to detect the anomalies.The proposed approach is validated with real wind farm data. [ABSTRACT FROM AUTHOR]

Abstract The aim of the present work is to study the influence of channel geometrical parameters on the performance of Savonius type hydrokinetic turbine and to present velocity correction methodology to determine the actual performance of the turbine. In the present experimental work, the effect of geometry of channel bottom and channel side wall distance on the performance of a Savonius turbine is investigated. Elevated channel bottom (hump) enhances the velocity of flow by reducing the depth of flow. Experimental results indicate that nearly an increase of 83% in power output is achieved by placing the turbine on the hump with reference to the turbine placed at the bottom of the channel. Similarly, the effect of channel sidewall location on the performance of turbine is studied for two separate cases, i. Constant flow rate - water spilling not allowed from blocked region and ii. Variable flow rate -water spilling over the blocked region allowed. In both the cases, the obtained coefficient of power is achieved above 0.45, considering the inlet velocity of flow. The results suggest that the potential head difference between the turbine inlet and outlet has the predominant effect on the power output of the turbine when a rotor is placed between the two closely located side walls. Considering the above facts, a new methodology is developed to find the corrected velocity to correlate the results obtained from restricted, high blockage canal flow with the performance which can be obtained from the same turbine when operated in a negligible blockage flow domain. Experimental results indicate that there is a vast variation in the maximum coefficient of power for all the cases studied if the velocity correction is not considered. However, with the application of the present velocity correction method, the corrected results are closer with the unblocked case. Highlights • Performance investigation of Savonius turbine is carried out for different channel blockage cases, by experimental approach. • Performance of same turbine evaluated when operated with different side wall distances and different heights of the hump. • The novel velocity correction technique developed using potential head change and validated for highly blocked channel flow. • Data are presented as coefficient of power and tip speed ratio along with the potential head change about turbine unit. • The correlation between potential head change and the corrected power coefficient is established in present investigation. [ABSTRACT FROM AUTHOR]

Abstract Winglets can reduce effect of wingtip vortices on the wind turbine performance can be reduced by diffusing the vortices from the blade tips. Unlike non-rotating wings, winglets have not been widely investigated for moving blades of wind turbines, while there is a potential they could enable the wind turbine rotor to capture more kinetic energy from wind. There have been a number of studies on the effect of winglet parameters and configurations on the wind turbine performance, however a combined effect of winglet planform and airfoil has not been investigated in details. The present work reports on the study of the effect of winglet planform and winglet airfoil on the wind turbine performance using Computational Fluid Dynamics (CFD). The National Renewable Energy Laboratory (NREL) phase VI rotor with 10 m diameter was used as the baseline and the CFD results were validated with the available experimental data on the output power and pressure coefficients. Different designs of winglet with different heights, cant angles, planforms and airfoils have been numerically tested and optimised. The best improvement in the performance is achieved when a 15 cm rectangular winglet with the S809 airfoil and 45° cant angle is used. Highlights • Effect of winglet planform and airfoil on wind turbine performance are studied. • An optimum winglet design has been found for the wind turbine blade in this paper. • The output power of wind turbine is increased using the optimum winglet design. • Extended blade can increase the thrust force. [ABSTRACT FROM AUTHOR]

Abstract A fully coupled nonlinear simulation tool using Morison's equation is developed to predict the dynamic response of floating offshore wind turbine (FOWT) system. Water tank tests are conducted to investigate hydrodynamic coefficients and the performance of the simulation tool under different sea states. Three issues are discussed in this paper. First, correction factors for the added mass and drag coefficients are proposed to account for the effects of frequency dependent hydrodynamic coefficients, and the effects of these correction factors on the global matrices are validated by the forced oscillation tests. Then, the effects of the frequency dependent hydrodynamic coefficients and the axial Froude-Krylov force on slender members are clarified by the free decay tests and water tank tests with regular and irregular waves. Finally, the dynamic behavior of mooring system on the fairlead tension is investigated by using quasi-static and dynamic models, respectively. The dynamic responses of FOWT with improved hydrodynamic models agree well with those measured in the water tank tests. Highlights • Correction factors for added mass and drag coefficients are proposed to account for frequency dependence of hydrodynamic coefficients. • Prediced dynamic responses of a semi-submersible floating offshore wind turbine by augmented Morison's equation show good agreement with the measured those. • The predicted fairlead tension by the dynamic model shows good agreement with the measurement than that by quasi-static model, and it sheds some light on the nonlinear coupling between the platform and the mooring line. [ABSTRACT FROM AUTHOR]

Abstract A new free-wake analysis for wind turbine aerodynamics is developed to accurately predict turbine performance and downstream wake evolution. A key feature is the Constant Circulation Contour Method (CCCM) which is a novel free-wake model for wind turbine wakes. This method characterizes a turbine wake by a number of resultant vortex filaments, avoiding the numeric artifact of a vortex lattice comprised of trailing and shedding vortices. The natural capture of wake roll-up and distortion using CCCM is illustrated and its computational complexity is demonstrated to be lower than Vortex Lattice Method (VLM). For accurate blade downwash calculation, a hybrid free-wake model is developed by combining CCCM with a VLM wake immediately behind turbine blades, which transitions to CCCM further downstream. Important properties of this hybrid wake are discussed and optimized to enhance model accuracy and efficiency. Blade static stall and unsteady effects are included. The hybrid model is validated through comparison to the wind tunnel experiments UAE Phase VI and MEXICO. Simulation examples are presented showing the utilization of this free-wake analysis to investigate wake steering, demonstrating the potential application of this method to wind farm scale wake simulations. Highlights • A novel free-wake model, Constant Circulation Contour Method (CCCM), is proposed. • CCCM efficiently predicts turbine wake evolution using resultant vortices. • A blade and near-wake Vortex Lattice Method includes stall and unsteady effects. • Validation with experiments shows excellent loads and flow velocity agreement. • Applicable to performance prediction, wake steering and wake shielding reduction. [ABSTRACT FROM AUTHOR]

Abstract Intensive condition monitoring of wind generation plant through analysis of routinely collected SCADA data is seen as a viable means of forestalling costly plant failure and optimising maintenance through identification of failure at the earliest possible stage. The challenge to operators is in identifying the signatures of failure within data streams and disambiguating these from other operational factors. The well understood power curve representation of turbine performance offers an intuitive and quantitative means of identifying abnormal operation, but only if noise and artefacts of operating regime change can be excluded. In this paper, a methodology for wind turbine performance monitoring based on the use of high-frequency SCADA data is employed featuring state-of-the-art multivariate non-parametric methods for power curve modelling. The model selection considerations for these are examined together with their sensitivity to several factors, including site specific conditions, seasonality effects, input relevance and data sampling rate. The results, based on operational data from four wind farms, are discussed in a practical context with the use of high frequency data demonstrated to be beneficial for performance monitoring purposes whereas further attention is required in the area of expressing model uncertainty. Highlights • The effectiveness of SCADA-based condition monitoring is negatively influenced by the low resolution of the 10-minute data. • A novel framework for wind turbine performance monitoring is presented, based on the use of high-frequency SCADA data. • The potential of high-frequency data for monitoring purposes is thoroughly investigated. • Wind turbine power curve is modelled using state-of-the-art multivariate nonparametric methods. • Sensitivity of power curve models to site specific conditions, seasonality, input relevance and sampling rate is studied. • The results demonstrate that using high-frequency data is beneficial for performance monitoring purposes. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the effects of lateral wind gusts on the aerodynamic performance of vertical axis wind turbines. A synthetic approach coupling computational fluid dynamics (CFD) simulations and the double multiple streamtube method is utilized to calculate vertical axis wind turbine performance. For simulating the wind gust response, the resolved gust approach (RGA) models the gust transport throughout the wind field. The effects of wind gusts on the effective wind velocity, angle of attack, torque and power performance are evaluated. The presence of gusts slightly changes the effective wind velocity and angle of attack. Lateral gusts increase the angles of attack in the upwind half period causing premature flow separations in the flowfield, while suppress flow separation by decreasing the angles of attack in the downwind period. The mean torque and power of the three-bladed turbines are enhanced by the lateral sharp-edge gust of 2 m/s by 5% in comparison to the steady wind. Reducing the number of blades to one and doubling the gust velocity make the performance further enhances by 14.7% and 34%, respectively. Finally, the effects of several gust shapes are investigated and discussed. Highlights • Wind turbine power output under gusts is calculated. • The process of gust passing wind turbines is simulated. • The method to calculate three-dimensional turbine performance is of low cost. • The effects of gusts on wind turbine performance are analyzed comprehensively. [ABSTRACT FROM AUTHOR]

Abstract The wake of upstream wind turbines is known to affect the operation of downstream turbines and the efficiency of the wind farm. In this study, a systematic experimentation on performance and wake spatial evolution was carried out using a wind turbine model varying tip speed ratio, pitch and yaw angles. The change of pitch angle was observed to induce a greater effect on the wake velocity as compared to the tip speed ratio. This is interpreted in terms of "force viewpoint", which describes more quantitatively the relationship between the turbine performance and the wake, as compared to the "power viewpoint", based on the sole energy conversion. The turbine yaw angle is observed to cause not only a decrease in power and thrust, but also an offset and an asymmetry in the wake. The offset, quantified using the spatial distribution of the velocity minima, is modeled analytically. Comparisons of model estimations with the experimental measurements show that the proposed model can acceptably predict the wake offset of a yawed turbine. The observed dependencies of the mean velocity deficit and wake turbulence on power, thrust, and yaw angle, may suggest new derating strategies for wind farm optimization. Highlights • A small-scale turbine model is tested under different operating conditions. • Different tip speed ratios, pitch and yaw angles are explored. • Velocity deficit, thrust and power coefficients are estimated. • A model to predict the wake offset for yawed turbines is proposed and validated. [ABSTRACT FROM AUTHOR]

This paper presents an experimental verification of the statistical time-series methods, which utilize adapted frequency response ratio (FRR), autoregressive (AR) model parameter and AR model residual as performance characteristics, for diagnosing the damage of wind turbine blades. Specifically, the statistical decision-making techniques are used to identify the status patterns from turbine vibration data. For experiments, a small-size, laboratory-used operating wind turbine structure is used. The performance of each method in diagnosing damages simulated by saw cut in three critical positions in the blade are assessed and compared. The experimental results show that these methods yielded a promising damage diagnosis capability in the condition monitoring of wind turbine. [ABSTRACT FROM AUTHOR]

This article provides a new methodology for wind turbine-site matching by using a probabilistic approach. The random behavior of the wind speed climate and the uncertainties of wind turbine characteristics are important to take into account in models used to evaluate the performance of the wind turbine. The proposed formulation of the wind turbine-site matching is derived based on the probabilistic reliability assessment approach. It was experimented using different power curve approximation models, for different random conditions, using time series of wind speed in two sites in Morocco: Dakhla and Essaouira. A comparison based on methods used in literature for the estimation of two-parameter of the Weibull function to fit the wind speed distribution is also carried out. The results revealed that the introduced performance indicators are less sensitive to the models used to approximate the wind power curves compared to the deterministic conventional indicator that leads to different rankings and problems of over-sizing or under-sizing. However, those performance indicators are more sensitive to the variation of the wind speed distribution parameter’s and can help on accurately estimate the wind power. Moreover, the proposed formulation allows a global sensitivity analysis using Sobol’s indices to observe the influence of each input parameter on the observed variances of the performance of a wind turbine. A numerical application illustrates the interpretation of sensitivity indices and shows the impact of the wind speed and the rated wind speed on the variance of the wind turbine performance. This method can help wind energy developers and manufacturers to optimally select WTGs for their future project and accurately forecast the performance of their WTGs for monitoring and maintenance scheduling under uncertainty. [ABSTRACT FROM AUTHOR]