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Wind energy production is growing rapidly worldwide in an effort to reduce greenhouse gas emissions. However, wind energy production is not environmentally neutral. Negative impacts on volant animals, such as bats, include fatalities at turbines and habitat loss due to land-use change and displacement. Siting turbines away from ecologically sensitive areas and implementing measures to reduce fatalities are critical to protecting bat populations. Restricting turbine operations during periods of high bat activity is the most effective form of mitigation currently available to reduce fatalities. Compensating for habitat loss and offsetting mortality are not often practiced, because meaningful offsets are lacking. Legal frameworks to prevent or mitigate the negative impacts of wind energy on bats are absent in most countries, especially in emerging markets. Therefore, governments and lending institutions are key in reconciling wind energy production with biodiversity goals by requiring sufficient environmental standards for wind energy projects.

This paper proposes a maintenance policy for a k-out-of-n: F system operating to fulfil several jobs without interruptions. The system is replaced when the Nth job completes or at the kth failure, whichever occurs first. So, there are some non-failed components when a replacement is done. These components can be sold as second-hand products to continue working in other systems for a while. The price of them is also considered in the proposed maintenance policy. An optimal maintenance policy is studied to minimise long-run average cost under the constraint of relative mean operating time. Comprehensive numerical studies are done to assess the effect of the model parameters on the optimal solutions. Also, to demonstrate the applicability of the proposed plan, a data set related to wind turbine generator failures is considered as a case study. [ABSTRACT FROM AUTHOR]

We examine the impact of proximity to land-based commercial wind turbines on residential home values in the United States using data on the universe of commercial wind turbines and residential property transactions from 2005 to 2020. Using event study and difference-in-differences identification strategies we find that, on average, homes located within 1 mile of a commercial wind turbine experience approximately an 11% decline in value following the announcement of a new commercial wind energy project, relative to counterfactual homes located 3 to 5 miles away. Event study estimates also reveal important dynamics in the evolution of home values, with property values first declining following project announcement, and then recovering post project construction, with property value impacts becoming relatively small (∼2%) and statistically insignificant 9 years or more after project announcement (roughly 5 years after operation began). Homes located within 1–2 miles of a commercial wind turbine experience much smaller impacts and homes located farther than 2 miles away are unaffected. Our results are primarily driven by wind projects located in urban counties with populations greater than 250,000.

Despite the number of works on the techno-economics of offshore green hydrogen production, there is a lack of research on the design of floating platforms to concomitantly support hydrogen production facilities and wind power generation equipment. Indeed, previous studies on offshore decentralised configuration for hydrogen production, implicitly assume that a floating platform designed for wind power generation (FOWT) can be also suitable as a floating wind hydrogen system (FWHS). This work proposes a novel design for an offshore decentralised FWHS, and analyses the effects of the integration of the hydrogen facilities on the platform's dynamics and how this in turn affects the performances of the wind turbine and the hydrogen equipment. Our findings indicate that despite the reduction in platform's stability, the performance of the wind turbine is barely affected. Regarding the hydrogen system, our results aim at contributing to further assessment and design of this equipment for offshore conditions. • Proposes a conceptual design of a decentralised floating wind-hydrogen system (FWHS). • Addresses key design differences with dedicated floating wind turbines. • Hydrodynamic aspects of FWHS assessed with state-of-the-art numerical tools. • Provides key performance indicators for offshore hydrogen production equipment. [ABSTRACT FROM AUTHOR]

The monopile-supported offshore wind turbines (OWTs) are subjected to the wave and current loadings. Affected by currents and waves, monopile-supported OWTs are also vulnerable to scour. However, the effect of scour and currents on the dynamic behavior of the monopile are not fully appreciated. This study conducted the model tests to evaluate the effect of scour depth and flow velocity on the lateral responses of support structure. Furthermore, the two-way (T-W) coupling fluid–structure interaction (FSI) method was proposed to evaluate the dynamic responses of piles in sand. The support structure is modeled using ABAQUS, a finite-element models software package, by considering the nonlinear soil–structure interaction effects, STAR-CCM + tools has been employed to model the FSI which are fed into ABAQUS to predict the structure's dynamic response. Using the proposed method, a parametric study has been conducted to evaluate the effects of scour depths, flow velocities on the dynamic responses of OWTs. The results indicate that scour altered the fundamental frequency of OWT, causing resonance. An increase in scour depth and flow velocity increased the dynamic responses of support structure, which are detrimental for the safety and stability of the OWT system. [ABSTRACT FROM AUTHOR]

The modified suction caisson (MSC) is a novel type of foundation for offshore wind turbines. Model tests and numerical simulations were conducted on the MSCs in sand to explore the lateral bearing behavior and variations of the rotation center position. Results show that the MSC can effectively increase the lateral bearing capacity and limit rotation compared with the regular suction caisson. For the MSC, the yield envelope slope at the 1/100 scale is equivalent to the slope at the 1/50 scale. Equations for the yield envelopes under different model scales were obtained. The internal compartment diameter and external structure length have a significant influence on the MSC lateral bearing capacity. Optimal dimensions of the MSC to maximize the bearing capacity were obtained: the ratio of the internal compartment diameter to the external structure diameter is greater than 0.4, and the ratio of the external structure length to the internal compartment length is within the range of 0.2 to 0.6. The rotation center of the MSC moves downward along the caisson embedded depth and moves forward in the loading direction with increasing angular rotation. As the angular rotation reaches 0.02 rad, the position of the rotation center tends to be stable. [ABSTRACT FROM AUTHOR]

This paper focuses on an innovative foundation type of monopile-friction wheel composite foundations, which aim to enhance the loading performance of offshore wind turbines (OWTs) while mitigating the negative impact of local scouring. The study utilizes numerical simulations to investigate the morphology of local scouring under unidirectional flow. Furthermore, the finite element method is employed to quantify the lateral bearing behavior, considering different scouring parameters, loading point heights, and pre-torsional loads. On this basis, the load bearing ratio of each part of the composite foundation under different scour conditions is also obtained. The results reveal that the horizontal bearing characteristics are significantly influenced by different scour parameters, loading point heights and pre-torsional loads. The local scouring can reduce the bearing capacity by about 38%, with scouring depth having the greatest effect, followed by the scouring angle and extent respectively. Moreover, as the loading point height and pre-torsional load increase, the lateral bearing behavior of composite foundations decreases. Notably, the friction wheel contributes more than 40% to the overall bearing capacity, underscoring its importance. The results provide valuable insights into further understanding the bearing behavior of the composite foundation and its potential engineering applications. [ABSTRACT FROM AUTHOR]

Monopiles are the economic choices in shallow water as the foundations of offshore wind turbines (OWTs). Maximum allowed rotation θ = 0.25° is set as the criterion in the serviceability limit state design. However, the allowed load combinations of monopiles in sand are not fully revealed and understood satisfying the criterion. In this paper, load envelop concept to ensure the allowed monopile rotation less than 0.25° was proposed to understand all possible load combinations on monopiles for the OWTs. Finite element models based on the sand hypoplastic model with inter-granular strain were established. After verification with the centrifuge results, different load–displacement curves were acquired by changing loading paths to acquire the envelope surfaces meeting the criterion. Finally, the most likely load combinations of the OWTs were particularly analysed. Under the condition with θ = 0.25°, the allowed horizontal loads and the bending moments are closely coupled. The calculated envelop curves composed of maximum allowed loads can be well fitted and described by the cubic function. This note provides a method to obtain load combinations with allowed inclinations, which is beneficial to understand the load states of monopile for OWTs. [ABSTRACT FROM AUTHOR]

To evaluate the seismic performance of a prestressed concrete-steel hybrid (PCSH) wind turbine tower, the seismic fragility curves based on incremental dynamic analysis (IDA) and multiple stripe analysis (MSA) on a two-scale model are presented and compared. The peak ground acceleration (PGA) and peak lateral drift on the top of the tower are adopted as the intensity measure (IM) and engineering demand parameter (EDP) of analysis, respectively. Finally, the seismic performance of the PCSH tower subjected to seismic action at different soil is investigated. The fragility curves obtained by IDA and MSA methods are compared. [ABSTRACT FROM AUTHOR]

Suction bucket jackets are increasingly being used to support bottom-fixed offshore wind turbines. It is generally assumed that contact between the underside of the bucket lid and the seabed is mandatory to safeguard against additional settlement. Lid contact is usually ensured by underwater grout injection, albeit this has a significant impact on the duration and costs of installation. Although grouting is routine, there are limited available data regarding the benefits of ensuring contact between the lid and the soil. This paper presents data from centrifuge tests of completely and partially installed buckets in dense sand subjected to vertical cyclic loading to investigate the role of lid contact. Lid contact was shown to have a discernible effect on displacement accumulation when buckets were loaded beyond the drained skirt capacity in compression. Under these conditions, settlement of a completely installed bucket was limited by lid contact with the soil plug, while partially installed buckets experienced continuous settlement, as expected. The physical evidence indicates complex load transfer mechanisms that are influenced significantly by the drainage conditions. Hence, an understanding of the soil drainage characteristics at a particular site would provide value when evaluating the requirement for under-lid grouting. [ABSTRACT FROM AUTHOR]

Small wind turbines (SWTs) can generate sufficient electricity to meet the energy needs of developing countries. However, due to the airflow characteristics at low Reynolds numbers and associated issues, specific airfoil designs are crucial to define the blade geometry. In this study, the lift coefficient (CL), stall angle of attack (AoA), and lift-to-drag coefficient ratio (CL⁄CD) of S1048, S3021, and S5010 airfoils and then optimized shapes with various thickness-to-camber ratio percentages (t/c%) were analyzed using XFOIL software to optimize their suitability for SWT applications. The aerodynamic efficiency of the optimized airfoils in terms of CL, drag coefficient (CD), CL/CD, and stall AoA was evaluated across Reynolds numbers ranging from 50,000 to 500,000. The findings revealed that these modified airfoils exhibited peak CL⁄CD values surpassing those of their baseline airfoils for the Reynolds number range of 50,000–500,000. The magnitudes of these improvements varied for each airfoil and at different Reynolds numbers. Additionally, the geometric modifications in terms of t/c% applied to the S1048, S3021, and S5010 airfoils resulted in enhanced maximum CL and stall AoA across all analyzed Reynolds numbers. [ABSTRACT FROM AUTHOR]

The focus of this study is on the aerodynamic design of a 2000-W airborne wind turbine (AWT) situated 100 m above ground level. AWTs harness higher wind speeds at higher altitudes, making them more efficient than ground-based turbines in generating power. To achieve the desired performance, numerical methods, such as blade element momentum (BEM) and computational fluid dynamics (CFD) were employed for the aerodynamic design and analysis of the AWT system. The rotor cross-section of the three-blade rotor incorporates S223 and S822 airfoils, which are derived from the conventional NREL airfoils. The diffuser section of the AWT has an elliptical curve to accommodate the maximum volume of helium gas. Through simulations using both CFD and BEM, the performance of the bare rotor was assessed, as well as the diffuser-augmented wind turbine (DAWT) under design and off-design conditions. The results demonstrated that the DAWT is capable of meeting the desired power output in all scenarios. Moreover, the findings indicated that using the diffuser enhances the rotor output power coefficient by 18% and prevents significant power loss during off-design conditions. This highlights the effectiveness of the rotor-diffuser assembly in maximizing power generation and ensuring consistent performance of the AWT system. [ABSTRACT FROM AUTHOR]

This research investigated dynamic vibration control in a monopile-supported wind turbine system through strategically placed resonators along its length. Four configurations were analyzed: Case 1 (conventional wind turbine model), Case 2 (resonators in the turbine tower), Case 3 (resonators in the monopile), and Case 4 (resonators in both tower and monopile). Utilizing spectral element formulations, the dynamic stiffness matrix was derived for the wind turbine system, embedded in cohesionless soil with frequency-dependent viscoelastic springs. Analytical responses at the tower top and monopile head under dynamic harmonic excitation were computed, and transmittance was determined as the logarithmic ratio of responses to input excitation. Experimental dynamic tests were conducted on a 3D-printed wind turbine scaled model, yielding displacement responses at the tower top and monopile head. Comparison with analytically determined transmittance values reveals consistent agreement across four configurations. Case 4 demonstrates substantial response reductions, highlighting the efficacy of resonators in both tower and monopile. Transmittance plots indicate notable response reduction near resonant frequencies, showcasing local resonance phenomena. Furthermore, the tower and monopile head responses are substantially reduced when the excitation frequency surpasses the resonator's natural frequencies. This underscores the dynamic vibration control capabilities of periodically positioned resonators within the wind turbine scaled model. The research also explores the influence of parameters such as resonator mass ratio, soil shear modulus, and pile and tower slenderness ratio on transmittance plots. [ABSTRACT FROM AUTHOR]

Flow control techniques used on wind turbines have been shown to significantly increase energy generation when compared to traditional wind turbines. Although various flow control methods have been introduced in the last two decades, the comparison between these methods is still the least conducted by researchers. Therefore, the present study aims to evaluate the performance of an airfoil utilizing both single and dual passive flow control methods, such as droop, flap, microcylinder, slot, and spoiler with optimal parameters. In this study, a numerical model was developed and applied with the same boundary conditions as those in the experiment. The results of the developed numerical simulation were then validated with experimental and other numerical studies. Mosaic mesh was utilized and the results were compared with conventional mesh types. Even though the mosaic mesh requires a lower number of computational elements, it demonstrated higher computational accuracy when compared to hexcore, polyhedra and tetrahedral type meshes. After obtaining an accurate numerical model, parametric studies were then conducted. The findings mainly highlighted that the airfoil with a microcylinder consistently generated higher performance than droop, flap, spoiler, slot and conventional airfoil. The mean relative improvement was about 2.6%. In an extensive study, eight combinations of flow controls were proposed and evaluated. The highest performances were achieved with the combination of microcylinder and flap, up to 27.9% and the combination of microcylinder and slot, reaching up to 50.2%, for low and high AOAs, respectively. [ABSTRACT FROM AUTHOR]

With the fast-growing demand for wind energy, small wind turbines are becoming a viable and cost-effective source of clean and renewable electricity for residential, businesses, small industries, and remote applications. To harness the maximum power, wind turbines (WT) should be operated at full capacity; hence, it is crucial to design an effective maximum power point tracking (MPPT) control scheme. This paper presents an effective MPPT control algorithm based on fuzzy logic control (FLC) which tracks the slope of the mechanical power of the WT as a function of the rotational speed. The output of this MPPT generates the duty cycle for the DC–DC converter to allow the WT to extract the maximum power under a wide range of wind speed and loading conditions. The electrical generator used in the studied wind energy conversion system is the permanent magnet synchronous generator (PMSG). The proposed FLC-MPPT strategy is simple to implement and does not require any prior knowledge of the WT parameters. The proposed FLC-MPPT technique for WT is simulated using MATLAB/Simulink and validated experimentally on a laboratory setup using a dSPACE1104 board. In addition, a comparison between the proposed FLC-MPPT and other methods under significant wind speed fluctuations and variable load conditions is presented to demonstrate its effectiveness. The results show that the proposed MPPT has a fast convergence with a high tracking accuracy and exhibits low steady-state oscillations. [ABSTRACT FROM AUTHOR]

Vibration is inevitable in operation of mechanical equipment, but severe vibrations will cause serious harm to wind turbines (WTs). This paper takes the drivetrain of 8 MW WT as the object, established a multi-body electromechanical coupling model of WT and verified the accuracy of the established model through the WT drivetrain in the laboratory. Subsequently, based on this model, time-frequency domain analysis was conducted on the vibration response of the WT drivetrain under different control strategies of the generator, and the influence of the generator control strategy on the vibration of the drivetrain was studied. The result shows that the generator control strategy has a significant impact on the vibration response amplitude of the drivetrain, but has a relatively small impact on the frequency component. Meanwhile, the sliding mode controller designed in this paper has good anti-interference ability, which can make the system quickly reach dynamic stability, and effectively suppress the vibration of the main components in the drivetrain. Under the new controller's control, the transverse vibration displacement of some parts of the WT drivetrain can be reduced by up to nearly 60 %. This paper provides new ideas and new methods for the active vibration reduction control of WT drivetrain. [ABSTRACT FROM AUTHOR]

Wind energy provides a sustainable solution to the ever-increasing demand for energy. Micro-wind turbines offer a promising solution for low-wind speed, decentralized power generation in urban and remote areas. Earlier researchers have explored the design, development, and performance analysis of a micro-wind turbine system tailored for small-scale renewable energy generation. Researchers have investigated various aspects such as aerodynamic considerations, structural integrity, efficiency optimization to ensure reliable and cost-effective operation, blade design, generator selection, and control strategies to enhance the overall performance of the system. The objective of this paper is to provide a comprehensive design and performance review of horizontal and vertical micro-wind turbines. The study begins with an overview of the current landscape of wind energy across the globe and India in particular, highlighting key challenges and opportunities. Numerical and experimental studies were used to validate the designs. Horizontal Axis Wind Turbines (HAWTs) with ducts or shrouds are suitable for microscale and low-speed applications. Researchers investigated the position and location of the turbines to enhance their performance in urban settings. Airflow and airfoil noise produce aerodynamic noise, which is the most significant disadvantage of wind turbines. The findings provide valuable insights for stakeholders interested in advancing micro-wind turbine technology. The highlighted research opportunities may be pursued further to improve the efficiency, reliability, and overall performance of micro-wind turbines. [ABSTRACT FROM AUTHOR]

Floating offshore wind (FOW) is a renewable energy source that is set to play an essential role in addressing climate change and the need for sustainable development. However, due to the increasing threat of climate emergency, more wind turbines are required to be deployed in deep water locations, further offshore. This presents heightened challenges for accessing the turbines and performing maintenance, leading to increased costs. Naturally, methods to reduce operational expenditure (OpEx) are highly desirable. One method that shows potential for reducing OpEx of FOW is LIDAR‐assisted pitch control. This approach uses wind velocity measurements from a nacelle‐mounted LIDAR to enable feedforward control of floating offshore wind turbines (FOWTs) and can result in reductions to the variations of structural loads. Results obtained from a previous study of combined feedforward collective and individual pitch control (FFCPC + FFIPC) are translated to OpEx reductions via reduced component failure rates for future FOW developments, namely, in locations awarded in the recent ScotWind leasing round. The results indicate that LIDAR‐assisted pitch control may allow for an up to 5% reduction in OpEx, increasing to up to 11% with workability constraints included. The results varied across the three ScotWind sites considered, with sites furthest from shore reaping the greatest benefit from LIDAR‐assisted control. This work highlights the potential savings and reduction in the overall levelised cost of energy for future offshore wind turbine projects deliverable through the implementation of LIDAR‐assisted pitch control. [ABSTRACT FROM AUTHOR]

Wind energy production is rapidly growing in the United States and is expected to continue increasing as more and larger wind turbines are installed. To support these taller and heavier onshore turbines, new foundations must be designed and manufactured. One proposed method of reducing the total amount of concrete and steel in spread foundations is to utilize additive manufacturing to enable more material‐efficient designs. To compare these additively manufacturing‐enabled designs to conventional foundation designs, this study performs a life cycle impact assessment of four ultra‐tall wind turbine foundations: two foundations using 78‐MPa 3D printed stay‐in‐place concrete formwork cast with 35‐MPa ready‐mix concrete with reinforcements, and two conventional foundations cast entirely out of 35‐MPa concrete with reinforcements. The life cycle assessment investigates the environmental impacts of four different stages, including materials production, transportation, construction, and end‐of‐life. The materials production stage is found to dominate the life cycle results, contributing over 97% of the total CO2 emissions and over 88% of the fossil fuel depletion for each foundation. Compared to the conventional designs, the Short Flat Ribbed Beam foundation with 3D printed formwork has 22.4% lower CO2 emissions and 28.3% lower fossil fuel depletion than the Circular foundation, and 2.0% higher CO2 and 5.9% lower fossil fuel depletion compared to the Tapered foundation. Parametric studies indicate that reducing cement content and increasing recycled content in printed concrete can significantly reduce the overall life cycle impacts of the foundations. [ABSTRACT FROM AUTHOR]

When planning a new wind farm, optimising the turbine layout to maximise power output is crucial. Traditional approaches based on analytical wake models often fail in complex terrain. In such areas, wake‐to‐wake interactions and terrain‐induced effects need to be taken into account via high‐fidelity optimisation. Building on our prior research on how best to maximise offshore wind farm power production by both micro‐siting (layout optimisation) and wake steering (yaw angle optimisation), this study focuses on the optimisation of two onshore wind turbines located around a 2D hill. The proposed approach is based on high‐fidelity simulations (LES) to account for the complexity of the flow and on Bayesian optimisation (BO) to systematically and efficiently find the optimal configuration for the two turbines given a set of parameters. The LES are performed with the high‐order finite‐difference wind farm simulator WInc3D, which has been modified for this study to deal with complex terrains and turbines with yaw and tilt. Following the validation of the immersed boundary method (IBM) and wall modelling used to model the complex terrain and of a modified actuator disc model (ADM) to account for tilted turbines, two BO campaigns are presented in this study, with different sets of parameters to optimise. The main flow features and some statistics for each optimum case are discussed using the flow fields with and without the optimised configuration of the upstream turbine to analyse its impact on the downstream turbine and on the overall power of the system. For the first optimisation, the design variables include the wind turbines' streamwise locations and their hub heights (4 parameters). This optimisation study benefits from an elevated upstream turbine hub, leading to a significant power increase in the downstream turbine, thanks to an acceleration of the flow in front of the hill. For the second optimisation, the design space is modified based on the data from the first optimisation, by replacing the turbine's hub height with the possibility of changing the tilt angle of the upstream turbine (4 parameters). It is found that considerable power gains can be obtained while maintaining a modest upstream turbine hub height, by introducing a positive tilt angle in the upstream turbine. Overall, it is found that by setting up the turbines in ways that exploit the speed‐up of the flow around the hill, both optimised layouts achieve considerable enhancements in power density over a reference configuration. [ABSTRACT FROM AUTHOR]

Recent studies have revealed the large potential of vertical‐axis wind turbines (VAWTs) for high‐energy‐density wind farms due to their favorable wake recovery characteristics. The present study provides an experimental demonstration and proof‐of‐concept for the wake recovery mechanism of the novel X‐Rotor VAWT. The phase‐locked flowfield is measured at several streamwise locations along the X‐Rotor's wake using stereoscopic particle image velocimetry (PIV) with fixed‐pitch offsets applied to the blades. The streamwise vortex system of the upper half of the X‐Rotor is first hypothesized and then experimentally verified. The induced wake deformations of the vortex systems are discussed in comparison with previous studies concerning traditional H‐type VAWTs. The results suggest that positive blade pitch is more favorable for accelerated wake recovery due to the dominant tip‐vortex generated on the upwind windward quadrant of the cycle. Utilizing theoretical blade load variations along the span explains distinct unsteady flow features in the near wake generated at select quadrants of the rotor rotation, shedding light on the potential of the two pitch schemes. [ABSTRACT FROM AUTHOR]

Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice. [ABSTRACT FROM AUTHOR]

This paper presents a graph‐based dynamic yaw model to predict the dynamic response of the hub‐height velocities and the power of a wind farm to a change in yaw. The model builds on previous work where the turbines define the nodes of the graph and the edges represent the interactions between turbines. Advances associated with the dynamic yaw model include a novel analytical description of the deformation of wind turbine wakes under yaw to represent the velocity deficits and a more accurate representation of the interturbine travel time of wakes. The accuracy of the model is improved by coupling it with time‐ and space‐dependent estimates of the wind farm inflow based on real‐time data from the wind farm. The model is validated both statically and dynamically using large‐eddy simulations. An application of the model is presented that incorporates the model into an optimal control loop to control the farm power output. [ABSTRACT FROM AUTHOR]

A versatile framework is introduced for determining optimal steady‐state operating points for wind turbine control. The framework is based on solving constrained optimization problems at fixed wind speeds and allows for systematically studying required trade‐offs and parameter sensitivities. It can be used as a basis for many control approaches, for example, to automatically compute optimal schedules for control inputs, steady‐state operating points for model linearization, or reference values for tracking. Steady‐state simulation results are obtained using full nonlinear models to consider complex effects caused by couplings from aerodynamics, structural dynamics, and possibly also hydrodynamics in the case of floating wind turbines. Focusing only on the steady‐state response allows a fast and numerically robust optimization, which makes it especially attractive for co‐design studies. The effectiveness of the framework is demonstrated on two offshore extreme‐scale wind turbines, one floating and one fixed bottom. [ABSTRACT FROM AUTHOR]

Flow modifications induced by wind turbine rotors on the incoming atmospheric boundary layer (ABL), such as blockage and speedups, can be important factors affecting the power performance and annual energy production (AEP) of a wind farm. Further, these rotor‐induced effects on the incoming ABL can vary significantly with the characteristics of the incoming wind, such as wind shear, veer, and turbulence intensity, and turbine operative conditions. To better characterize the complex flow physics underpinning the interaction between turbine rotors and the ABL, a field campaign was performed by deploying profiling wind LiDARs both before and after the construction of an onshore wind turbine array. Considering that the magnitude of these rotor‐induced flow modifications represents a small percentage of the incoming wind speed (≈3%), high accuracy needs to be achieved for the analysis of the experimental data and generation of flow predictions. Further, flow distortions induced by the site topography and effects of the local climatology need to be quantified and differentiated from those induced by wind turbine rotors. To this aim, a suite of statistical and machine learning models, such as k‐means cluster analysis coupled with random forest predictions, are used to quantify and predict flow modifications for different wind and atmospheric conditions. The experimental results show that wind velocity reductions of up to 3% can be observed at an upstream distance of 1.5 rotor diameter from the leading wind turbine rotor, with more significant effects occurring for larger positive wind shear. For more complex wind conditions, such as negative shear and low‐level jet, the rotor induction becomes highly complex entailing either velocity reductions (down to 9%) below hub height and velocity increases (up to 3%) above hub height. The effects of the rotor induction on the incoming wind velocity field seem to be already roughly negligible at an upstream distance of three rotor diameters. The results from this field experiment will inform models to simulate wind‐turbine and wind‐farm operations with improved accuracy for flow predictions in the proximity of the rotor area, which will be instrumental for more accurate quantification of wind farm blockage and relative effects on AEP. [ABSTRACT FROM AUTHOR]

The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models. [ABSTRACT FROM AUTHOR]

A principal challenge facing the control of floating offshore wind turbines (FOWTs) is the problem of instability, or "negative damping," when using blade pitch feedback to control generator speed. This closed‐loop instability can be attributed to non‐minimum phase zeros in the transfer function from blade pitch to generator speed. Standard approaches to improving stability and performance include robust tuning of control gains and introducing multiple feedback loops to respond to platform motion. Combining these approaches is nontrivial because multiple control loops complicate the impact of coupling in the system dynamics. The single‐loop approach to analyzing stability robustness neglects inter‐loop coupling, while a simplistic multi‐loop approach is highly sensitive to dimensional scaling and overestimates the robustness of the single‐loop controller. This work proposes a sensitivity representation that separates some of the natural FOWT dynamic coupling into a parallel feedback loop in the sensitivity function loop to address both of these concerns. The modified robustness measure is used with a simplified linear FOWT model to optimize scheduled multi‐loop control parameters in an automated tuning procedure. This controller is implemented for the 10‐MW Ultraflexible Smart FLoating Offshore Wind Turbine (USFLOWT) and compared against conventional single‐ and multi‐loop controllers tuned using frequency‐domain analysis and high‐fidelity OpenFAST simulations. The multi‐loop robust controller shows the highest overall performance in generator speed regulation and tower load reduction, though consideration of power quality, actuator usage, and other structural loading leads to additional trade‐offs. [ABSTRACT FROM AUTHOR]

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large‐eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross‐verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large‐scale meteorological models as boundary conditions. [ABSTRACT FROM AUTHOR]

Large‐eddy simulation (LES) has been adopted to study wind turbine wakes because it can capture fine‐scale details of turbulent wind flows and interactions with wind turbines. Here, we use the LES version of the Weather Research and Forecasting (WRF) model with an actuator disk model to gain insights on several wake effects that have been traditionally difficult to measure. The first finding is that the wake has a "dual nature," meaning that the wind speed deficit behaves differently from the added turbulent kinetic energy (TKE) and the two are not co‐located in space. For example, the wind speed deficit peaks at hub height and reaches the ground within 8D (D is the rotor diameter), but added TKE peaks near the rotor tip and generally remains aloft. Second, temperature changes near the ground are driven by the added TKE in the rotor area and by atmospheric stability. The combination of these two factors determines the sign and intensity of the vertical heat flux divergence below the rotor, with convergence and warming associated with stable conditions and weak divergence and modest cooling with unstable conditions. Third, wakes do not expand indefinitely, as suggested by similarity theory applied to the wind speed deficit, but eventually stop expanding and actually contract, at different rates depending on atmospheric stability. The implication of these findings is that, in order to study wakes, it is not sufficient to focus on wind speed deficit alone, because TKE is also important and yet behaves differently from the wind speed deficit. [ABSTRACT FROM AUTHOR]

Simulating entire wind farms with an actuator line model requires significant computational effort, especially if one is interested in wake dynamics and wants to resolve the tip vortices. A need to explore unconventional approaches for this kind of simulation emerges. In this work, the actuator line method is implemented within a lattice‐Boltzmann flow solver, combined with a sliding mesh approach. Lattice‐Boltzmann solvers have advantages in terms of performance and low dissipation, while the sliding mesh allows for local refinement of the blade and tip vortices. This methodology is validated on a well‐documented case, the NREL Phase VI rotor, and the local refinement is demonstrated on the NREL 5 MW rotor. Results show good agreement with reference Navier–Stokes simulations. Advantages and limitations of the sliding mesh approach are identified. [ABSTRACT FROM AUTHOR]

The aim of this research is to evaluate the performance of the distribution network by connecting wind distributed generation (DG) and determining the optimal location and size using the particle swarm optimization (PSO) technique, once the wind DG is connected at the optimal location, the output of wind turbines is not constant but varies with changes in wind speed. Wind turbines are designed to generate the energy from the wind. As the output of the wind turbines changes, it influences the power flow and voltage levels in the distribution network. The injection of power from the wind turbines can cause variations in voltages within the distribution network. Additionally, the changing power flow may contribute to power losses in the distribution system. In this paper, the voltages and active power losses are evaluated with the change in wind speed for the IEEE 15 Bus system by conducting load flow analysis in MATLAB. The results reveal optimized solutions that contribute to reduced power losses, increased renewable energy generation, and improved voltage profiles. This research underscores the potential of PSO-based optimization in conforming more efficient and sustainable distribution networks. [ABSTRACT FROM AUTHOR]

The ongoing advancement of wind turbines, aiming for taller towers to harness more intense winds, poses substantial structural challenges. Soil‐structure interaction (SSI) assumes fundamental importance, necessitating precise analysis, and mathematical modeling. This study focuses on examining how SSI influences horizontal‐axis wind turbine tower‐foundation systems. Six numerical models, varying from simplified to more complex representations, are created using the finite element method (FEM) in ANSYS software. The analysis reveals significant sensitivity to support conditions, particularly elastic supports, causing the greatest displacement at the tower's top (1.899 m), highlighting the substantial influence of SSI and second‐order effects. Incorporating SSI and second‐order effects results in a 30.11% increase in von Mises stress at the base flange (73.4 MPa), compared to models excluding these factors. Stress variation along the tower height notably increases with second‐order effects; however, the structure maintains a 13.32% safety margin relative to steel load‐bearing capacity. Foundation analyses indicate stresses exceeding concrete's allowable stress by 24.3%, underscoring the need for foundation optimization. These results stress the importance of considering SSI and geometric nonlinearity for wind turbine development. The lack of comparable studies in literature underscores the significance of this research in advancing the field's knowledge. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the accuracy of predicting the aerodynamic loads and investigate the aerodynamic wake characteristics of a vertical axis wind turbine (VAWT) rotor using a simplified two-dimensional numerical rotor model and an advanced numerical approach – the Scale Adaptive Simulation (SAS) coupled with the four-equation γ – Reθ turbulence model. The challenge for this approach lies in the operating conditions of the rotor, the blade pitch angles, and the very small geometric dimensions of the rotor. The rotor, with a diameter of 0.3 m, operates at a low tip speed ratio of 2.5 and an extremely low blade Reynolds number of approximately 22.000, whereas the pitch angles, β, are: -10, 0, and 10 degrees. Validation was conducted based on high-fidelity measurements obtained using the PIV technique at TU Delft. The obtained results of rotor loads and velocity profiles are surprisingly reliable for cases of β = 0° and β = –10°. However, the 2-D model is too imprecise to estimate both aerodynamic loads and velocity fields accurately. [ABSTRACT FROM AUTHOR]

In response to the global shift toward renewable energy, wind energy is a pivotal player in sustainability. Floating offshore wind turbines (FOWTs) emerge as a promising solution for expanding wind energy into economically challenging deep waters. Despite their potential, challenges persist, necessitating a thorough understanding of the complex coupling effects between wind turbine aerodynamics and hydrodynamics, particularly during the design phase. This study highlights this critical need and extends its scope to review the relevant existing literature. The paper provides insights into the design considerations and assessment methodologies crucial for both new structures and the evaluation of existing ones. Through modeling in the Ashes wind turbine software, the study reveals that platform surge motion significantly impacts rotor performance, causing rotor power and thrust fluctuations. By comparing various wind and sea states with baseline testing, the study underscores the necessity of coupling aerodynamic and hydrodynamic forces for accurate performance predictions. Besides, the paper offers actionable recommendations for designing and optimizing FOWTs, and sheds light on the challenges and opportunities within offshore wind energy, offering valuable guidance for engineers working toward sustainable energy solutions. [ABSTRACT FROM AUTHOR]

Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector Machine (SVM), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), we investigate the impact of average wind speed on stress transfer function and fatigue damage in wind turbine structures. Our findings indicate significant precision levels exhibited by GRNN and SVM, making them suitable for practical implementation. CSNN demonstrates superiority over BPNN and PSO-ANN in predicting blade fatigue life, showcasing enhanced accuracy, computational speed, precision, and convergence rate towards the global minimum. Furthermore, CNN and NARX models display exceptional accuracy in classification tasks. These results underscore the potential of ANNs in addressing challenges in wind turbine monitoring and fatigue detection. However, it's important to acknowledge limitations such as data availability and model complexity. Future research should explore integrating real-time data and advanced optimization techniques to improve prediction accuracy and applicability in real-world scenarios. In summary, this review contributes to advancing the understanding of ANNs' efficacy in wind turbine monitoring and fatigue detection, offering insights and methodologies that can inform future research and practical applications in renewable energy systems. [ABSTRACT FROM AUTHOR]

The wind farm layout optimization problem (WFLOP) is a significant problem in the field of renewable energy. In this development of wind farm, solving the WFLOP is a crucial task, which entails placing the turbines in the wind farm in the best locations to reduce wake effects and enhance predicted power generation. In recent decades, the WFLOP problem has been solved mathematically. Meanwhile, the growing load demand led to an increase in the complexity of WFLOP. The results obtained by mathematical methods were not accurate enough to suit complexity of WFLOP. Nowadays, researchers from a variety of fields are developing nature‐inspired algorithms (NIAs) to solve difficult real‐world problems. This study is an attempt to review the most important innovations in the field of NIAs to solve the WFLOP problem. The classification of the reviewed literature is based on different applied approaches and models. In addition to specific proposals, the advantages and disadvantages of certain domains are also discussed. This study provides a future direction to the fellow researchers who are working in the field of WFLOP. [ABSTRACT FROM AUTHOR]

The steel–concrete hybrid tower (SCHT) has been popularized as the supporting structure for onshore wind turbines to meet the increasing hub height and rotor diameter. The internal force of the cross-section, which is the prerequisite of the structural design, is based on the load analysis. However, the nonignorable effect of the second-order gravity makes analyzing the external load of the supporting tower a coupled problem, especially for the SCHT, which is higher than a conventional steel tubular tower. Besides, the aerodynamic load of the wind turbine, the main excitation acting on the supporting tower, is usually computed by numerical methods and lack of validation. To optimize the analysis method for the internal force of the SCHT, one feasible approach is evaluating the external excitation directly. Based on the theory of the Kalman filter, this study develops a dynamic inverse method of the SCHT. It aims to estimate the horizontal thrust of the wind turbine and provide an overall evaluation of the dynamic responses of the SCHT by using the measured dynamic responses at the limited point on the SCHT. A rigorous numerical simulation based on ABAQUS is conducted to generate the dynamic responses of the SCHT, which are used to validate the effectiveness of the proposed method. It also investigated the influence of observation type, number of measuring points, and noise level on the estimation accuracy. [ABSTRACT FROM AUTHOR]

The stand-alone wind-energy storage integrated hydrogen production technique is becoming a key and emerging technique to achieve carbon neutrality. However, the conflict between the random wind power fluctuation and the stable power demand of the electrolyzer lowers the system's operation stability and reliability. To address this issue, a modified output power smooth control strategy for the wind turbine that considers the dynamic performance of the electrolyzer is proposed. The output power of the wind turbine can be smoothed following the need of the electrolyzer, which helps reduce the electrolyzer's start-stop times and the battery's charging and discharging cycles. Eventually, the efficiency and life span of the hydrogen production system is enhanced. Afterward, an operational strategy for the hydrogen production system is provided, and a coordinated sizing strategy for the wind turbine, energy storage system, and electrolyzer is proposed. The results of case studies, which use the real data obtained from a hydrogen production demonstration project, prove that the overall lifecycle revenue for the hydrogen production system is remarkably increased. Finally, a long-term simulation model for a stand-alone wind-energy storage integrated hydrogen production system was developed. Simulation results validate the effectiveness of the proposed method. • The proposed method smooths wind turbine power in line with electrolyzer dynamics. • A coordinate sizing method fully considering practical factors is constructed. • The proposed method can reduce the electrolyzer's annual shutdown time by 4.37%. • The proposed method can help increase the annual hydrogen production by 6.06%. • The proposed method can help enhance the overall lifecycle revenue by 32.92%. [ABSTRACT FROM AUTHOR]

Synchronous stability is crucial for the safety and operation of AC power systems. However, most of the current researches focused on the stability of grid‐connected converters, and that of renewable equipment still lacked. In this article, the impact of the additional inertia control (AIC) on the permanent magnet synchronous generator (PMSG) is studied. It is found that with the AIC, the machine‐side converter dynamics of the PMSG cannot be ignored, and the system dominant dynamics shifts from the electromagnetic to electromechanical timescales. This article develops a simplified model for the single‐PMSG infinite‐bus system with the AIC within the electromechanical timescale, and reveals the transient synchronization stability mechanism from three aspects: the machine‐network interface, transient dominant variable, and interaction between the synchronization loop and the power imbalance loop. Finally, this article analyzes the swing characteristics of the PMSG system, and uncovers the relationship between the energy transmission and synchronization. These findings are supported by wide experimental verification and can provide the deeper physical insight and theoretical basis for the transient synchronous stability analysis of renewable‐dominated new‐type power systems. [ABSTRACT FROM AUTHOR]

A major obstacle standing in the way of full‐scale adoption of renewable energy sources is their intermittency and seasonal variability. To better understand the power generation dynamics, the effect of air density due to temperature on power and energy generation figures was modelled. The model uses historical ERA5 data and considers changes in weather patterns in a subarctic climate where seasonal changes are most pronounced. The power generation figures of using a mean and a dynamic air density value were compared and the results show that power generation estimates may be under‐ and overestimated by on average 5% up to 10% in winter and summer, respectively. This can have implications for the sizing of power transmission infrastructure and energy storage in both on‐grid and off‐grid applications as well as power availability. The topic is highly relevant in the Nordic countries where roughly 10% of new global added wind capacity is installed annually. [ABSTRACT FROM AUTHOR]

Continuous fault ride‐through (CFRT) issues often arise in wind power systems. CFRT results in continuous voltage fluctuations which is characterized by "initially decreasing and then increasing" and can significantly disrupt the normal operation of wind power systems. To mitigate CFRT related problems, one approach is the utilization of energy storage (ES) based dynamic voltage restorers (DVRs). Nevertheless, the prohibitive costs and substantial ES requirements hamper practical implementation. In this article, a control scheme incorporating adaptive mode switching and coordinated control is proposed. First, the adaptive mode switching control leverages the advantages of two DVR compensation methods to reduce the injected voltage amplitude. The mode switching is activated by the DC link voltage and utilizes the PQR transformation to unlock the phase‐locked loop (PLL). Subsequently, an adaptive coordination coefficient is introduced, which considers the margin of ES regulation power and rotor inertia, to maintain power balance during CFRT. This proposed control strategy not only enables wind turbines to seamlessly ride through continuous faults without disconnecting from the grid but also leads to a reduction in the ES compensation requirement. To validate the effectiveness of the proposed approach, simulations based on Simulink and hardware‐in‐loop (HIL) experiments are conducted. [ABSTRACT FROM AUTHOR]

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made. [ABSTRACT FROM AUTHOR]

In vibration testing of civil engineering structures, the first two vibration modes are crucial in representing the global dynamic behavior of the structure measured. In the present study, a comprehensive method is proposed to identify the first two vibration modes of wind turbine towers, which is based on the analysis of fractional order statistical moments (FSM). This study offers novel contributions in two key aspects: (1) theoretical derivations of the relationship between FSM and vibration mode; and (2) successful use of 32/7‐order displacement statistical moment (Md32/7)$( {M_d^{32/7}} )$ as the optimal FSM to identify wind turbine tower modes, by combining with noise resistance analysis, sensitivity analysis, and stability analysis, respectively. Using the proposed method, the FSM was first used to identify the modal vibration of wind turbine towers. By obtaining the response of the structure on the same vertical line, FSM was then calculated to estimate the corresponding structural modal vibration. Considering other influencing factors in the field test, the modal identification results of this index under different excitation forms and noise conditions were analyzed based on numerical simulation and verified with field wind tower test data. The results of the evaluation show that the proposed statistical moments of Md32/7$M_d^{32/7}$ can accurately identify the first two vibration modes of wind turbine towers. This presents a new robust method for modal vibration identification, that is, simple and effective in its implementation. [ABSTRACT FROM AUTHOR]

Changing environmental conditions and measured noises often affect the dynamic responses of structures and can obscure subtle changes in the vibration characteristics caused by damage. To address this issue, a new method for classifying damage in offshore structures under varying environmental conditions and measured noises is proposed using linear discrimination analysis (LDA). Two sets of data on dynamic characteristics, one from healthy structures and the other from unknown testing structures, are used to determine the optimal projection vector. This vector is perpendicular to the discriminant hyperplane and is used for damage classification. The damage‐sensitive features are extracted by projecting both sets of data onto this vector. These features are then used with the hypothesis test technique to determine the condition state of the testing structure. Numerical studies on offshore wind turbine structures and experimental validations of a deep‐sea mining system are being conducted to evaluate the effectiveness of the proposed approach. The study also examines the impact of mode combinations, measured noises and samples on the performance of the approach. The results indicate that the proposed approach can accurately assess the structural health state even in the presence of environmental changes and noise contamination, even with limited samples. The promising performance of the approach will facilitate the establishment of an online structural monitoring system to ensure the safety of offshore structures. [ABSTRACT FROM AUTHOR]

ABSTRACT Experimental evidence indicates that multidimensional cyclic loading of soils causes larger accumulation of deformations than equivalent one‐dimensional loading. The response of sand to high‐cyclic loading with 10,000 cycles and up to four‐dimensional stress paths (i.e., four independent oscillating components) is examined in 120 triaxial and hollow cylinder tests in this work to extend these findings. With increasing number of oscillating stress components, the accumulation of permanent strains tends to increase. It is demonstrated that the definition of the multidimensional strain amplitude incorporated in the high‐cycle accumulation (HCA) model can account for this. The validation of the HCA model for complex cyclic loading is complemented by the simulation of model tests on monopile foundations of offshore wind turbines subjected to multidirectional cyclic loading, for which the consideration of spatially variable cyclic loading with nonconstant load amplitudes in the HCA model is discussed. For this purpose, an extension of the HCA model considering multiple strain amplitudes is presented. [ABSTRACT FROM AUTHOR]

Improving wind power generation efficiency and lowering maintenance and operational costs are possible through the early and efficient diagnosis and repair of surface defects in wind turbines. To solve the lightweight deployment difficulty and insufficient accuracy issues of the traditional detection methods, this paper proposes a high-precision PC-EMA block based on YOLOv8 using partial convolution (PConv) combined with an efficient multiscale attention (EMA) channel attention mechanism, which replaces the bottleneck layer of the YOLOv8 backbone network to improve the extraction of target feature information from each layer of the network. In the feature fusion phase, GSConv, which can retain more channel information, is introduced to balance the model's complexity and accuracy. Finally, by merging two branches and designing the PConv head with a low-latency PConv rather than a regular convolution, we are able to effectively reduce the complexity of the model while maintaining accuracy in the detection head. We use the WIoUv3 as the regression loss for the improved model, which improves the average accuracy by 5.07% and compresses the model size by 32.5% compared to the original YOLOv8 model. Deployed on Jetson Nano, the FPS increased by 11 frames/s after a TensorRT acceleration. [ABSTRACT FROM AUTHOR]

The research objective in the context of the study relates to the major concern of corrosion affecting the wind turbines in operation to find materials with high durability in relation to environmental conditions of operation, strength, and cost. A method is an integration of the Analytical Hierarchy Process (AHP) and VIKOR Multi-Criteria Decision Making (MCDM) techniques that will assess seven different material options on sixteen criteria that comprise corrosion resistance, mechanical properties, cost, and a negative environmental impact. From this result, the AHP method calculated the weights for the indicators and chose potential materials, and finally, the VIKOR method used these materials and compared and ranked them to obtain a compromise solution. The research novelty integrates the AHP and VIKOR MCDM methods to address corrosion in wind turbines. By evaluating seven materials against challenging sixteen criteria—including corrosion resistance, mechanical properties, cost, and toxicity, AHP ranks and weights the criteria, while VIKOR identifies the optimal material choice. This dual approach enhances the selection process, ensuring the chosen material improves turbine performance and durability, offering a significant advancement in the sustainable development of wind energy technology. In conclusion, by integrating AHP and VIKOR, it comprehensively evaluates multiple material options based on corrosion resistance, mechanical properties, cost, and environmental impact. This methodology effectively identifies materials that enhance wind turbine performance and extend their lifespan, addressing a critical industry challenge. The alternative exhibits a similarity to the positive ideal solution (Si) of 0.3704 and a relative closeness to the ideal solution (Ri) of 0.0750. Additionally, its priority ranking (Qi) is 0.001, placing it in the first rank for Carbon Fiber Reinforced Polymers (CFRP) within the selection methodology. [ABSTRACT FROM AUTHOR]

AbstractStratified sampling is one of the powerful variance reduction methods for analyzing system performance, such as reliability, with stochastic simulation. It divides the input space into disjoint subsets, called strata, to draw samples from each stratum. Partitioning the input space properly and allocating greater computational effort to crucial strata can help accurately estimate system performance with a limited computational budget. How to create strata, however, has yet to be thoroughly examined. Strata design faces the curse of dimensionality and data scarcity as the input dimension increases. We analytically derive the optimal stratification structure that minimizes the estimation variance for univariate problems. Further, reconciling the optimal stratification into decision trees, we devise a robust algorithm for multi-dimensional problems. Numerical experiments and a wind turbine case study demonstrate the superiority of the proposed method in terms of variance reduction, leading to computational efficiency and scalability. [ABSTRACT FROM AUTHOR]