Wind Industry Research Articles

Detecting wire breaks in post-tensioned tendons of wind turbines: A signal energy spectrum analysis approach

In the wind industry, recent advancements have led to the research and development of wind turbines featuring hybrid towers, a novel combination of steel tube and precast concrete segments. These concrete modules, which absorb the high stresses caused at the intersection between the tower and its foundation, are commonly joined with post-tensioned tendons. This study focuses on the identification of wire breaks in post-tensioned tendons through the application of acoustic emission testing. Measurements involve the evaluation of wire breaks under controlled laboratory conditions and the analysis of the dynamic operational environment of a functioning wind turbine. The investigation encompasses the development and assessment of a methodology based on principles of discrete Fourier transformation and Parseval’s theorem for analyzing the frequency-dependent energy distribution of acoustic signals. This analytical approach extends to the examination of wire breaks generated under varying stress levels as well as the operational noise within the actual wind turbine. The findings demonstrate a notable concentration of energy within the frequency range of 5-20 kHz in the wire break signals. In contrast, the operational noise signals show a distinct pattern, presenting an extreme value distribution within the 0-2 kHz range. The developed methodology exhibits robustness, even in the presence of high background noise levels, establishing itself as a valuable tool for wire break detection. Additionally, its potential for integration with machine learning algorithms offers the prospect of automated wire break detection, enabling further advancements in structural health monitoring for wind turbines.

Minimization of wire-wound pressure vessel diameter based on distortion energy theory

This paper investigates the minimization of the diameter of wire-wound pressure vessels. The study is conducted in two stages. Firstly, the stresses arising from the wire winding of the vessel and the internal pressure application are extracted based on the distortion energy theory. It is assumed that the equivalent stress within the winding area in each layer, under the internal pressure condition, equals the allowable stress of the wire, and in the cylinder area, it does not exceed the allowable stress of the cylinder. The required number of layers and the wire tension during winding (two essential unknown parameters in the industrial winding process) are determined to satisfy these assumptions. In the second stage, the diameter optimization of the vessel is studied using the Distortion Energy (DE) theory. It is found that reducing the cylinder diameter results in a decrease in the vessel diameter. The occurrence of buckling or yielding in the cylinder is a limiting constraint for reducing the cylinder diameter. For validation, the results obtained from the derived equations are compared and confirmed against finite element results and the equations provided in the ASME code. Wire-winding simulation around the cylinder uses the element birth and death technique. The agreement between the derived equations and the code equations, as well as finite element results, is excellent. In the examined case study, using the DE theory leads to a 24 % reduction in wire consumption compared to the maximum shear stress (MSS) theory. In the optimization stage, the vessel weight is further reduced by 24 %. Compared to monobloc shells, the optimized wire-wound vessel weight based on the DE theory experiences a 77 % reduction.

Quantifying circular economy pathways of decommissioned onshore wind turbines: The case of Denmark and Germany

Onshore wind turbines in Europe are increasingly reaching the end of their first lifecycle. Their pathways after decommissioning call for the establishment of circular supply chains (e.g. refurbishment or recycling facilities). Reliable component and material flow forecasts are particularly crucial for the development of blade-recycling capacity, as such facilities still need to be established. However, current forecasts assume a static decommissioning time and neglect a second lifecycle for the wind turbines and their blades, which has resulted in potential recycling quantities being over-estimated. This study overcomes these issues by (i) collecting empirical data on the circular economy pathways taken by decommissioned onshore wind turbines in the mature onshore wind markets of Denmark and Germany, and by (ii) proposing a new component and material flow forecasting model for the more reliable planning of blade-recycling capacity. The results reveal that ∼50–60 % of decommissioned onshore wind turbines in Denmark and Germany were exported mainly to other European countries. If the second lifecycle practices of the past are continued in the future, annual blade masses for domestic recycling are expected to range between ∼380–770 tonnes for Denmark and ∼4400–11,300 tonnes for Germany in the next ten years. This study finds that the threshold values of blade volumes for an economically viable blade-recycling facility can be reached in Germany with its large operating wind-turbine fleet, but the recycling of Danish wind turbine blades would have to rely on aggregating resource flows from other countries or industries. By modelling the cascading order of a sustainable circular economy and the EU Waste Hierarchy Directive, this study improves the decision-making basis for policy makers and companies to achieve sustainable resource use along the wind industry's entire value chain.

Regulations for Bat Protection in Mexico's Wind Farms

Wind energy development has expanded the fastest globally among all renewable sources during the last 20 years. However, wind farms have documented adverse impacts on bats, including mortality from collisions with turbine blades and disruptions to habitat and behavior. As the world's sixth most attractive economy for renewables, with 70 operating wind farms, Mexico and its bats now face escalating threats from the country's burgeoning wind industry. Despite this rapid growth, few studies have analyzed Mexico's regulatory framework to prevent, evaluate, and mitigate wind farm effects on bats. In this study, we reviewed Mexican laws and treaties that facilitate wind farm permitting, construction, operation, and decommissioning, and searched for guidelines that specifically address bat conservation. We found eight international pacts that promote wind power adoption along with three relevant articles in Mexico's Constitution. The General Law of Ecological Balance and Environmental Protection proved most pertinent for impact management. Supplementary guidelines from the Ministry of Environment and Natural Resources offer general strategies for evaluating wind farm impacts on bats, but adherence remains voluntary. Given expanding wind power investments across Mexico, we highlight the need for more stringent national standards that require preventative and corrective measures to protect bat populations. Tighter legislation and enforcement offer pathways toward environmentally sustainable wind energy development in Mexico.

Wake steering experiments in onshore and offshore wind farms

Over the past years, wake steering has been the subject of much research in the wind industry. Multiple academic publications have shown results from high fidelity simulations (such as SOWFA), engineering simulations (such as FLORIS) or from field tests. Most of this research is focused on the power increase as it is the main goal of wake steering. However, other key topics need to be covered upfront. Wake Adapt is the product developed by Siemens Gamesa Renewable Energy that applies wake steering at commercial level. As presented in this paper, some prerequisites are needed before Wake Adapt installation to ensure the wind turbines are calibrated to apply the optimum yaw offsets. The increase in energy is not without costs: yaw activity is increasing which impacts the maintenance costs. Wake Adapt loads must be assessed, and it has been shown that Wake Adapt loads cases are covered by design loads of the turbines. On the modelling side, the Wake Adapt yaw offsets are generated using some engineering models well known by the scientific community. Some robustness is added to the Yaw Offset Lookup Table to ensure that the optimum yaw offsets calculated in steady-state conditions are still optimum with unsteady conditions. Finally, in order to measure the Wake Adapt benefit, a Swap Test can be conducted where wind farm power output with and without Wake Adapt are compared following a certain procedure, especially if the predicted and measured power benefit needs to be compared. The last section of this paper shows some first tests in an onshore wind farm, as well as the results of a full Swap Test in an offshore wind farm, where the measured gain and the predicted gain shows very similar values.

Floaters upscaling for multi-megawatt floating wind turbines

The floating wind industry requires wind turbines with increasing power ratings, which will require bigger platforms. However, few floater concepts are publicly available for numerical simulation of future wind turbines. To overcome this limit, this work proposes a fast and straightforward upscaling methodology to upscale already available floating platforms to greater wind turbine power ratings. The methodology does not aim to optimize the floater design, but it can generate realistic floater data for preliminary numerical simulations. The methodology is applied here to four floaters: a semisubmersible, a barge, a TLP and a spar. The platforms are upscaled for a 15 MW wind turbine and a specific deployment site. The upscaling methodology is adapted for each floater since some differences arise from one platform to the other. Whenever possible a comparison with already existing 15 MW substructures is proposed and commented.

Digitalization of Large-Scale Testing Facilities for the Wind Industry: DIGIT-BENCH Digital Twin

Testing of large wind turbine components plays a central role in delivering reliable yet cost-effective technology. However, these experiments are often lengthy and costly. Fatigue testing of a wind turbine blade might take up to 12-14 months, whereas highly accelerated lifetime testing of a nacelle demands 6-8 months. The exchange of simulation models and data between OEMs and test facilities is recognized as a critical factor in the planning of an experimental campaign. In fact, OEMs are typically very protective of their industrial secrets, and sharing such sensitive information may constitute a threat. It follows that the use of simulation models to enable more effective experimentation is not pursued efficiently.Digital twins are emerging as a key enabling technology to improve the operation & maintenance of test benches for the wind industry. A digital twin combines physical systems and their digital models into a cyber-physical system to provide functionalities that cannot be attained by either physical or digital assets independently. The seamless integration of the test bench with digital models offered by a digital twin is expected to enhance the interaction between OEM and test bench operators.This proceeding illustrates the status of the development of the DIGIT-BENCH digital twin developed by R&D Test Systems (R&D) and Aarhus University to serve large-scale test facilities for the wind industry. The digital twin utilizes FMI-based co-simulation to enable the coupling of physical/digital components in an industrial-secret-friendly environment. The digital twin concept is demonstrated on a 2-degrees-of-freedom test bench installed at Aarhus University.

A multi-fidelity approach for wind farm simulations and comparison with field data

The prediction of energy production and structural loads within wind farms is of high interest for wind industries to optimize the wind farm design and control under a variety of atmospheric conditions. However, it is still a key challenge to predict them accurately and efficiently due to the complex interactions between wind turbines and turbulent flows. Nowadays, high-fidelity simulations using Reynolds-Averaged Navier-Stokes (RANS) or Large-Eddy Simulation (LES) coupled with actuator disk or actuator line method are widely developed and used in wind farm analysis, but it still needs a huge computational resource, especially in the application of a commercial wind farm with large number of turbines. In this context, a mid-fidelity simulation tool based on the Dynamics Wake Meandering (DWM) model called FAST.Farm has been developed by National Renewable Energy Laboratory (NREL) in order to tackle this challenge. It allows to capture essential physics at the turbine scale as well as at the farm scale in a computational efficient manner. This study focuses on the calibration of DWM model which is the key to minimize inaccuracies between mid-fidelity and high-fidelity simulations regarding key performance indicators, e.g. thrust and power production. The calibration is made for DTU10MW wind turbine and shows a good improvement in accuracy compared to default parameters. The calibrated DWM model is finally employed to forecast the power generation for two turbines within a reference wind farm. A good improvement on the prediction is also obtained thanks to the calibrated parameters.

Modeling of Blockage and Wake Effect: Comparison with Field data

We apply engineering approaches for estimating the induction zone in front of a wind turbine and escalating to the global blockage at wind farm and cluster of farms scale as well accounting for wind farm wake. The methods include the vortex cylinder model and the self-similar model for blockage, and Jensen and Eddy-viscosity models for the wake estimation. To calibrate each model, Reynold Average Navier-Stokes with Actuator disc simulations are employed. Every model’s efficacy is assessed in comparison to the validation data of an operated wind farm in Scotland with more than 100 turbines of 10 MW each. We also examine the widely used process within the wind industry for transferring the application of calibrated wake and blockage models from one wind farm. According to our simulation analysis, blockage causes sideways acceleration and upstream slowdown. This also result in a gradient in the power produced by each turbine on the farm, which, if not properly accounted for, appears to be a wake model constraint. Furthermore, the response of different turbine type in another environment is not effectively predicted by the blockage and wake model, which is based on a particular turbine type and environment.

Comparison of line-of-sight wind speed measurements from an X-band radar and a long-range scanning lidar

As a still novel wind measurement technology, a dual-Doppler X-band wind radar system has been a substantial element of the full-scale onshore campaign AWAKEN (The American WAKE experimeNt). In order to select suitable further applications in the future and, particularly, the most optimal use cases in the wind industry for this technology, a line-of-sight wind speed verification campaign using a co-located scanning lidar as reference was set up as part of the AWAKEN campaign. The wind radar scanned in azimuth sector or plan position indicator (PPI) mode, with multiple elevations (volumetric PPI scan), while the scanning lidar remained fixed in a specific position during the verification campaign. Considering the individual spatial and temporal resolutions of the two systems, the closest points from the radar scanned volumes were compared with measurements from the scanning lidar after threshold-based and statistical data quality control. For a linear regression with 30-minute resolution data collected at 2 km range, a coefficient of determination of R 2 = 0.99 was found. Radar mean values, binned according to reference wind speed, do lie in part within the reference uncertainty but not consistently for the investigated range of line-of-sight wind speeds. Part of the reference uncertainty is hereby also associated with the procedure of comparison but kept as low as possible by optimizing the verification setup and procedure.

A developed soil reaction model for large- diameter monopiles in sand based on hyperbolic curves

Given the preference as the foundation for offshore wind turbines, this paper focuses on large-diameter monopiles and presents a series of finite element analyses to investigate the response to lateral loads. The contribution of four soil reactions, including distributed lateral load (p-y), distributed moment (m-θ), and base shear force and base moment, to the lateral resistance encountered by monopiles is quantified. It can be found that apart from the distributed lateral load, the contribution of distributed moment exceeds 14 %, while the proportion of base shear force and base moment is less than 5 % and is considered negligible. This research investigates how the diameter and embedded length of monopiles impact the load-bearing characteristics. A 'p-y + m-θ' model based on the two-parameter soil reaction curve is proposed. This model is not only straightforward and easy to use for engineering design but also considers the effect of rotational deformation on the soil reaction curves. Additionally, a relationship between ultimate lateral soil resistance and relative density is established, leading to an analysis model suitable for sands of various relative densities. Finally, the model effectively predicts the load–displacement relationship for large-diameter monopiles under lateral loads, providing valuable support for monopile design in the offshore wind industry.

GREENER IS CHEAPER: AN EXAMPLE FROM OFFSHORE WIND FARMS

Abstract Offshore wind farms (OWF) are now in operation and increasingly under construction as scalable, sustainable energy sources. In fact OWFs are currently the cheapest form of new energy projects in Europe. The levelized cost of energy (LCOE) for OWF has fallen drastically due to decades of innovation facilitated by both taxpayer and private sector funding. This emerging industry is experiencing massive worldwide growth with the potential to accelerate the decarbonization of regional and the global economy as well as bring a reliable source of green hydrogen into commercial use, all with minimal disruption to ecosystems and impacts on biodiversity. This paper provides a historical perspective of wind energy harnessing and shows that wind turbines are the oldest, largest and one of the smartest machines. We also highlight the potential of offshore wind energy to provide new solutions to (a) meet clean energy demand for a growing world population, (b) improve energy security of nations through other downstream technologies such as production and storage of dispatchable fuel (such as green hydrogen battery storage) and (c) through supply complementarity improve resilience of nuclear power plants in high-seismic-activity areas. Offshore wind industry can also become a gold standard for future industries, and the paper provides insights into the new green economics and jobs and factories for the future. We show that environment-friendly regulation is driving innovations even further to enhance sustainability of OWF. Examples include material recycling, landfill ban on blade disposal and ecofriendly low-noise offshore construction to protect biodiversity.

Assessing the engineering, environmental and economic aspects of repowering onshore wind energy

As onshore wind farms approach the end of their life, critical decisions about their future become imperative. Wind turbine repowering projects encounter multifaceted challenges across economic, engineering, environmental, and social domains. This study critically examines the state of the art in onshore wind repowering on a global scale. The potential of repowering onshore wind to achieve three key objectives is investigated: enhancing energy output, extending operational life, and contributing to net-zero targets. The analyses reveal significant increases in generation capacity through repowering, with benefits extending to local economies and emissions reduction. Additionally, technological advancements such as variable hub heights and wind turbine classes offer optimization opportunities for repowering projects. Challenges such as time-limited consents and financial disincentives prompt an examination of the complexities inherent in these issues and the opportunities they present. The study analyses the complicated interactions of engineering, environmental, and economic factors on a global scale. To overcome these challenges, the study recommends implementing stable financial support mechanisms, streamlining regulations through adaptive energy laws, and enhancing public engagement. Emphasising sustainable practices, the paper calls for clear legislative frameworks focused on wind turbine recyclability and collaborative efforts between the wind industry and communities to ensure environmentally responsible repowering projects.

Experimental evaluation of the short and long fatigue crack growth rate of S355 structural steel offshore monopile weldments in air and synthetic seawater

Welded steel structures used in the offshore wind industry are exposed to harsh marine environments, which can result in corrosion-induced fatigue damage. Of particular concern is the heat affected zone (HAZ) of welded joints, a region known for its altered microstructure and mechanical properties, which can significantly influence the initiation and propagation of fatigue cracks. This study investigates the short and long fatigue crack growth rates, and the effect of seawater exposure, for the HAZ in S355 steel weldments. Single-edge notch bend (SENB) specimens are used, with a shallow notch in the HAZ. A series of specimens is immersed in synthetic seawater that is continuously circulated at a controlled temperature to assess the synergistic effects of corrosion and fatigue. The experimental method integrates a novel application of front face strain compliance for monitoring short cracks, alongside an extended back-face strain compliance approach for monitoring long crack propagation. It is concluded that the short fatigue crack growth rate of the HAZ is 2.7 to 3.5 times higher in seawater as compared to air. As the crack propagates and enters into the long crack regime, the ratio decreases to 2.2 times at the transition point of the two-stage crack growth curve and further decreases to 1.5 times when the notch advances towards fracture. The findings indicate that the fatigue crack growth rates documented in standards tend to be on the conservative side. This study significantly enriches the fatigue crack growth data available in literature, which will contribute to a more accurate lifetime assessment offshore wind turbine structures.

Review and analysis of the failure risk mitigation via monitoring for monopile offshore wind structures

Structural health monitoring systems are gaining more attention in the offshore wind industry as they offer valuable insights into the integrity status of operating assets. Whilst most Class Society Rules and International Standards recognise the importance of implementing a condition-based maintenance strategy, they only provide theoretical guidance. Ultimately, it is the asset owner’s responsibility to determine how to integrate this strategy into their broader operation and maintenance planning, including identifying which components to monitor and which monitoring techniques to employ. The present paper applies the Failure Mode, Effects, and Criticality methodology to identify the most critical failure modes to prioritise for monopile offshore wind structures. Hence, the potential benefits of incorporating structural health monitoring systems within a condition-based maintenance strategy and exploiting lifetime extension possibilities are assessed. To achieve this, a novel 4-step methodology is introduced, involving understanding failure mechanisms (time-dependent behaviour and pattern), current regime (inspections at intervals), monitoring options (both direct and indirect), improvement potential evaluation through 5 key performance indicators relevant for optimal O&M, which is more comprehensive and realistic than considering only monetary consequence of failure. The study addressed the prevailing failure modes in 5 categories, namely fatigue, corrosion, deformation, buckling and displacement, and connection failure, aiming to demonstrate potential improvement in terms of risk mitigation against these failure modes. The results of this study can significantly help offshore wind developers optimise where and how to allocate their resources for structural health monitoring, resulting in long-term cost reduction opportunities.

Assessing the effects of anemometer systematic errors on wind generators performance by data-driven techniques

Systematic measurement errors frequently affect the anemometers installed on wind turbines, reducing the generator conversion efficiency, and resulting in significant discrepancies between the expected and the observed annual energy production. Despite these critical effects, the literature appears to lack a comprehensive focus on this topic. To address this research gap, this study proposes a novel data-driven multi-step methodology aimed at detecting systematic measurement errors in wind turbine anemometers and assessing their impacts on the generated power profiles. The proposed approach leverages the analysis of operation data of wind turbines by detecting their performance deterioration and divides a wind farm in potentially anomalous and normal wind turbines. Then, a data-driven regression model predicts the wind speed measured by the anomalous wind turbines as a function of the measurements collected at the normal wind turbines and, through the analysis of the residuals between model estimates and measurements, the systematic anemometer error is identified and its onset is correlated with a performance drop. Experimental data from 11 industrial wind turbines during an observation period of 10 years are elaborated to assess the effectiveness of the proposed framework. For the selected test case, anemometer errors ranging between 0.36 and 0.43ms-1 have been identified, to which a loss of at least 3% and up to 7% of the yearly producible energy is estimated to be associated. Such data analysis inspired the on-site inspection, which confirmed the results of this work.

Benefits of Mann–Kendall trend analysis for vibration-based condition monitoring

Rank-based statistics offer an appealing framework to non-parametric robust trend detection. Especially, the Mann–Kendall test detects the presence of a trend in a series. This paper investigates the benefits of using the Mann–Kendall test, which seems to have remained largely unnoticed in the context of vibration-based condition monitoring. Two contributions structure the present paper. First, theoretical foundations of rank-statistics are reminded and the Z-score is introduced, a statistical metric measuring the presence of a trend in a given series. The performance of the Mann–Kendall test is investigated and confronted to different numerical cases involving series of increasing condition indicators. Second, based on this understanding, the Z-score metric is exploited to design two trend-oriented signal processing tools dedicated to vibration-based condition monitoring. Namely, a new tool named the Mannagram is introduced as a dyadic filterbank representation of the trend of indicators series. It shows effective in the informative band selection problem and unveils more interpretable indicators. Besides, a concise representation of trend by frequency bin is introduced and coined the Kendrum. This representation is shown to help the diagnosis by summarising the trend information of series of spectra. Both methods are demonstrated on run-to-failure series of vibration signals from industrial wind turbines.

The multi-scale coupled model: a new framework capturing wind farm–atmosphere interaction and global blockage effects

Abstract. The growth in the number and size of wind energy projects in the last decade has revealed structural limitations in the current approach adopted by the wind industry to assess potential wind farm sites. These limitations are the result of neglecting the mutual interaction of large wind farms and the thermally stratified atmospheric boundary layer. While currently available analytical models are sufficiently accurate to conduct site assessments for isolated rotors or small wind turbine clusters, the wind farm's interaction with the atmosphere cannot be neglected for large-size arrays. Specifically, the wind farm displaces the boundary layer vertically, triggering atmospheric gravity waves that induce large-scale horizontal pressure gradients. These perturbations in pressure alter the velocity field at the turbine locations, ultimately affecting global wind farm power production. The implication of such dynamics can also produce an extended blockage region upstream of the first turbines and a favorable pressure gradient inside the wind farm. In this paper, we present the multi-scale coupled (MSC) model, a novel approach that allows the simultaneous prediction of micro-scale effects occurring at the wind turbine scale, such as individual wake interactions and rotor induction, and meso-scale phenomena occurring at the wind farm scale and larger, such as atmospheric gravity waves. This is achieved by evaluating wake models on a spatially heterogeneous background velocity field obtained from a reduced-order meso-scale model. Verification of the MSC model is performed against two large-eddy simulations (LESs) with similar average inflow velocity profiles and a different capping inversion strength, so that two distinct interfacial gravity wave regimes are produced, i.e. subcritical and supercritical. Interfacial waves can produce high blockage in the first case, as they are allowed to propagate upstream. On the other hand, in the supercritical regime their propagation speed is less than their advection velocity, and upstream blockage is only operated by internal waves. The MSC model not only proves to successfully capture both local induction and global blockage effects in the two analyzed regimes, but also captures the interaction between the wind farm and gravity waves, underestimating wind farm power by about only 2 % compared with the LES results. Conversely, wake models alone cannot distinguish between differences in thermal stratification, even if combined with a local induction model. Specifically, they are affected by a first-row overprediction bias that leads to an overestimation of the wind farm power by 13 % to 20 % for the modeled regimes.

Enhancing fatigue reliability prediction of offshore wind turbine jacket joints through individual uncertainties for each degree of freedom of stress concentration factor

This paper presents the fatigue reliability prediction for welded planar tubular joints of offshore fixed jacket support structures. A coupled model is employed to calculate the dynamic response of the jacket support structure under wind and wave loads. Stress concentration factors (SCFs) are evaluated using Efthymiou parametric equations, and the hot-spot stresses at eight locations on the chord and brace of the tubular joints are derived by summing the stress components from axial, in-plane, and out-of-plane actions. The stress distribution is determined using the rainflow counting method, fatigue damage from an S–N curve, and Miner’s rule. Uncertainties associated with the fatigue lifetime evaluation procedure are identified, quantified, and modeled. The focus is specifically given to modeling the uncertainty related to the SCFs, and a framework is proposed to evaluate the fatigue reliability of the joint by incorporating individual uncertainties for each degree of freedom of the SCFs (i.e., axial load crown, axial load saddle, in-plane bending moment, and out-of-plane bending moment). The results reveal that assuming the same uncertainty level (Coefficient of Variation of 0.2) as recommended by DNV-RP-C210 for each degree of freedom of the SCFs and including the uncertainty after obtaining the stress distribution from rainflow counting does not consistently yield conservative reliability index values, as it depends on the critical hot spot. It is essential to note that the simplified assumptions derived from the oil and gas sector may not directly translate to the offshore wind industry due to differences in loading conditions. A reduction of up to approximately 24% in the reliability index is observed for one critical hot spot, while an increase of up to 20% was observed for another. Overall, this paper provides valuable insights into the complex interplay of factors affecting the reliability of joints in offshore fixed jacket support structures, shedding light on the need for tailored approaches to address uncertainties in the specific context of the offshore wind industry.

Feasibility study on preloaded flexible conical plain bearings as wind turbine main bearings

Wind turbines (WT) are a key technology towards a carbon neutral energy production worldwide. Currently about 30 % of the Levelized Cost of Electricity (LCoE) consist of service and maintenance. Critical components are the main roller bearings which have a failure probability between 15 and 30 % within 20 years. Main bearing replacements are expensive maintenance procedures because an external crane is needed which cost about $250.000 per day for offshore WTs. Hence, a discussed countermeasure within the wind industry is to use segmented plain bearings in future WTs. These types of bearings allow an up-tower sub-component wise replacement of faulty parts without the need to dismantle the whole drivetrain. Therefore, the Chair for Wind Power Drives (CWD) developed, tested and validated a segmented conical plain bearing concept for the use as a main bearings for WTs. To function properly common plain bearings need a minimum clearance to allow the formation of a convergent lubrication gab. This initial clearance negatively influences run-out, as the shaft con move freely within the limits of the clearance. As WT drivetrain concepts become more integrated, main bearings for WTs need to fulfill higher requirements regarding the allowable run-out of the main shaft. Therefore, a fundamental design challenge arises for plain bearings as rotor main bearings. One approach to reduce run-out for roller main bearings is to use preloaded tapered roller bearings. For common plain bearings however preloading is not possible. However, the concept of preloading was successfully transferred to the flexible conical plain bearing concept developed at the CWD and the main shaft run-out severely reduced. In this work the feasibility of a preloaded flexible conical plain bearing as a WT rotor main bearing is evaluated and the advantages and disadvantages contrasted.