Wind Turbine Manufacturers Research Articles

Compare Industrial Development Between China and America: Centered on Wind Turbine Production

With the impact of climate change on the planet, wind energy has become a key part of the shift from fossil fuels to clean energy. Over the past decade, the wind energy industry has experienced rapid growth, with the production of wind turbines expanding to meet the growing demand. This expansion is not only a testament to advances in wind turbine design and manufacturing technology, but also a global commitment to increasing the share of renewable energy in the overall energy mix. On the one hand, wind energy, as a renewable energy source, plays a crucial role in reducing carbon emissions as it is capable of generating electricity without producing harmful emissions or depleting natural resources. Unlike fossil fuels, wind energy is abundant, widely distributed and sustainable in meeting the world's energy needs. Wind energy helps to reduce carbon emissions, improve air quality and minimize water consumption compared to conventional methods of power generation.

Why project success in manufacturing digitalization remains elusive: charting the way forward

Purpose There is substantial evidence that Industry 4.0-enabled manufacturing projects frequently encounter slow progress or failure due to organizational misalignment. This paper demonstrates the relevance of adopting a socio-technical approach when engaging in such projects.Design/methodology/approach A single embedded case study was conducted in a large wind turbine manufacturer, analyzing 42 digital manufacturing projects from 2018 to 2023 using interviews and surveys. A descriptive analysis identified patterns in successful projects, and hypotheses concerning relationships between variables were evaluated through regression analysis. In terms of theoretical conceptualization, the study adopts a socio-technical lens.Findings The study reveals relevant and targeted aspects for developing a socio-technical approach to guide the implementation of digital manufacturing projects. Our findings demonstrate that digital manufacturing projects exhibit diverse socio-technical configurations, each involving various social variables that contribute to project success. Through our proposed approach, we demonstrate how applying this framework can reveal patterns that drive project success.Originality/value This study represents one of the initial efforts to clarify an approach for evaluating diverse socio-technical project configurations by demonstrating it in a real-world context.

Pivoting B2B Platform Business Models: From Platform Experimentation to Multi-Platform Integration to Ecosystem Envelopment

The landscape of digital servitization in the manufacturing sector is evolving, marked by a strategic shift from traditional product-centric to platform business models (BMs). Manufacturing firms often employ a blend of approaches to develop business-to-business (B2B) platforms, leading to significant reconfigurations in their BMs. However, manufacturing firms frequently encounter failures in their B2B platform development initiatives, leading them to abandon the initial efforts and/or pivot to alternative platform strategies. Therefore, this study, through an in-depth case study of a leading wind turbine manufacturer, articulates a three-phase pivoting framework for B2B platform BMs with corresponding platform development and strategic orientation. Initially, a manufacturer focused on asset-based product sales, supplemented by asset maintenance services, follows an emergent platformization strategy, characterized by the rise of multiple, independent B2B platforms catering to diverse functions. Next, focusing on the imposed customer journey strategy, the firm shifts towards an imposed and strategic multi-platform integration into an all-encompassing platform supported by artificial intelligence (AI), signaling a maturation of the platform BM to combine the wide range services into an energy-performance-based contract. Finally, the last step of the firm’s platform BM evolution consists of a deliberate open platform strategy to external stakeholders and enveloping its offerings in a broader platform ecosystem. The study showcases advanced AI applications that process wind farm, wind turbine, and blade data, signifying a transformative leap toward value capture via platform ecosystem. The paper advances B2B platform BMs and digital servitization literature, highlighting a progressive approach's efficacy and strategic pivoting.

Implementing Crowbar Protection To Maintain System Stability In Doubly Fed Induction Generator Wind Turbines

Doubly fed induction generator (DFIG) wind turbines play a crucial role in wind energy production. However, system stability during symmetrical voltage dips remains a significant challenge. This research area focuses on enhancing protection and regulation strategies to ensure that DFIG wind turbines operate stably and efficiently even when the electrical grid experiences disturbances. In-depth simulations and behavioral analyses are utilized to propose effective control solutions, minimizing the impact of voltage dips without compromising system stability. The findings from these studies are essential for wind turbine manufacturers and operators, contributing to the overall improvement of wind energy systems.

Technical specification IEC/TS 61400-11-2: measurement of wind turbine noise characteristics in receptor position - an overview

To facilitate the development of wind energy, a Technical Specification has been developed by the IEC project team PT61400-11-2, giving guidance on how to assess the noise characteristics from a wind farm in the surroundings through measurements and assessment at the receptor position. This includes physical characteristics like sound pressure levels, wind speed, amplitude modulation, tonality, amongst others. In writing the Technical Specification, the expert group intended to collect experience and knowledge from existing methods and standards. The TS is written as an operational guideline for conducting measurements for authorities and measurement institutes, tailored to the specific intentions of the measurements. It will be of particular interest in countries where no guidance on wind farm noise measurements is available but also in countries where guidance and legislation of environmental noise measurements may not be sufficiently adapted for wind turbine noise specifics. An overview of the content of the document will be presented along with the considerations and choices made during extensive discussions by the international expert group stemming from acoustic measurement institutes, wind turbine manufacturers, wind farm developer, site operators and academia.

Collaboration or competition? Interactions between floating and fixed-bottom offshore wind in Norway

Fixed-bottom offshore wind is exploited as a maturing technology in many European countries. Floating wind has impressive potential for deep waters but needs technological and market development. How these two partially related technologies interact remains unclear. We address the ambiguity of these interactions to investigate floating offshore wind's development. The interactions are divided into technological or market and can be negative (competition and resistance) or positive (collaboration and diversification). We analyze these interaction types through a case study of offshore wind in Norway. Many positive interactions were observed, including knowledge overlaps and infrastructure compatibilities. Negative interactions include competition about future space constraints at ports, labor availability, and resistance by incumbent wind turbine manufacturers. Further, market and technological interactions are mutually influential, creating important feedback loops. Technologies can no longer be simply categorized as ‘niche’ or ‘regime’, but rather ‘niche-like’ (emerging) and ‘regime-like’ (maturing); hence, both emerging-emerging and emerging-maturing interactions occur.

Adhesive Snap-Fit Joints for Modular Wind Turbine Blades: A Numerical Feasibility Study

Larger rotor diameters are sought by wind turbine manufacturers as they favour cost-effective energy generation. However, manufacturing, transporting, and installing longer blades gets increasingly complicated, time-consuming, and costly. While a potential solution lies in spanwise segmentation, available modular blade technologies are still relatively immature, have drawbacks, and are yet to be used for blades exceeding 80 meters. A key challenge to blade segmentation is the addition of joints, which can result in both structural as well as aeroelastic penalties, when comparing segmented designs to their monolithic counterparts. To tackle these issues, in this study, we present the proof of concept and initial feasibility of an adhesively bonded snap-fit joint. The study assesses the joint’s load carrying capacity under quasi-static loading conditions at two levels: first, at the component level, focusing on the snap-fit elements, and second, at the system level, examining the integration of these components into the blade section. Under the specified assumptions, the results highlight the hybrid joint’s capability to withstand substantial loads of the order of magnitude required to meet operating requirements.

Introducing a partial bottom-up model for onshore wind turbine CAPEX estimation

European wind turbine manufacturers are under significant cost pressure. To minimize risk in investment and development decisions, it is crucial to identify cost drivers, especially given the high volatility of resource prices. This study presents a cost model that breaks down the component costs of onshore horizontal axis gearbox or direct drive wind turbines. Individual sub-models are developed for each component, using existing models where available. Production costs of steel towers, rotor blades and gearboxes are modeled, following a bottom-up approach. The calculated main investment costs for a 4.4 MW onshore wind turbine in 2023 are 1311 €/kW. These results are approximately 15 % higher than those of a previous study conducted in Germany in 2022. The increase is attributed to price developments, high inflation, and the fact that manufacturers have been selling turbines at a loss, thus underestimating turbine costs in the recent past. The model is a valuable tool for researchers, OEMs, and policy makers to analyze manufacturing and material costs. It facilitates informed decision-making about future research needs in the face of economic challenges.

Developing onshore wind farms in Aotearoa New Zealand: carbon and energy footprints

ABSTRACT In recognition of deeper insights into the implications of wind farm deployments, this paper addresses the need for an updated Life Cycle Assessment (LCA) for onshore wind generation systems, using 4.3 MW wind turbines and direct drive permanent magnet synchronous generators. The environmental and energy performances were estimated through an LCA for an onshore wind plant under construction in Aotearoa New Zealand with a total nameplate capacity of 176 MW. This study used real construction data showing literature data overestimates civil works and underestimates transportation contributions in the wind farm footprint. Further, different end-of-life management alternatives for turbine blades are analysed: landfill, mechanical recycling, and chemical recycling. The results indicate a carbon footprint of 10.8–9.7 gCO2eq/kWh, a greenhouse gas payback time of 1.5–1.7 years for avoided combined cycle gas turbines, and an energy payback time of 0.4–0.5 years, in which the chemical recycling of the blades is the lower emission solution overall. The outcomes underscore the environmental efficiency of onshore wind farms and their important role in the energy transition. Notably, the manufacturing of wind turbines is the primary contributor to the carbon and energy footprints, highlighting a critical area for targeted environmental mitigation strategies.

Research on the optimization of tribological performance of wind power lubricating grease based on carbon emission

The manufacturing, installation, operation and dismantling of wind turbines can also have environmental impacts such as excessive carbon emissions and consume large amounts of resources. Optimisation of the tribological properties of wind power greases can reduce the energy consumption and carbon emissions of wind power systems, improve their operational efficiency and reliability, thereby slowing down climate change and improving environmental quality, which is not only important for individual wind power projects, but also has a positive impact on reducing carbon emissions, promoting clean energy development and combating climate change on a global scale. However, the higher the grease lubrication performance, the lower the wind turbine failure rate and the lower the carbon emissions. Good tribological properties can significantly reduce the coefficient of friction of mechanical components, reducing surface wear and heat generation, helping to extend the life of mechanical equipment, improve efficiency and reduce unnecessary repairs and replacements. Therefore, in this paper, Mobil SHC 461WT lithium composite grease was mixed with molybdenum dialkyl dithiocarbamate (RFM3000), nano-boronated rare-earth friction modifiers (SK3115), polysiloxane viscosity modifier (PV611), and zinc dialkyl dithiophosphate (ZDDP), and the comparative analysis of their tribological performances was carried out through the method of cross-experimentation. The results showed that the average coefficient of friction of Mobil added with the four antiwear additives was reduced by 74 %, 41 %, 54 % and 48 %, respectively, and the average diameter of wear spots was reduced by 64 %, 63 %, 69 % and 54 %.

Using the petiole of the miriti palm for the core of a small wind turbine blade

In many small wind turbine blades, the interior space between laminate skins is filled by a material core. The mechanical properties of the core are much less important than its density, which must be low to reduce the moment of inertia as high inertia increases both the starting time of the turbine and the gyroscopic loads on the blades. In this paper, we use, for the first time, the petiole of the miriti palm (PMP) as the core of four small blades, in order to analyze its effect on turbine starting performance. PMP is abundant in the Amazon region and harvesting it does not destroy the palm because the petiole regrows; therefore, harvesting is fully sustainable and may well have a major role in increasing the sustainability on wind turbine manufacturing. We consider the benefits of using the easily worked petiole for the core in terms of manufacturing, as demonstrated by the construction of a 0.598 m blade. PMP is less dense on average than alternative materials, such as expanded polystyrene and balsa wood. The starting performance is an important issue for small wind turbines. It is evaluated using a quasi-steady model, in which blade element momentum theory is coupled to Newton's Second Law. The low density of the small blade made using petiole of the miriti reduces the starting time by 10% when compared with expanded polystyrene and 42% when compared to balsa wood.

A Fully Integrated Simulation Approach of Drive Trains towards Tonality Free Wind Turbines

Wind turbine manufacturers are now facing stricter noise regulations as turbines are being placed closer to urban areas. While rotor blade aero-acoustic noise is the dominant noise component in the total sound pressure level of a wind turbine, mechanical noise originating from gears and generators are gaining importance as well, especially when producing tonal noise. To minimize the tonal noise originating from the gears it is crucial to compare different drivetrain concepts and gear designs early in the design phase and consider the NVH performance as part of the design selection criteria. Unfortunately, the software available on the market allows the prediction of the acoustic performance of a drivetrain design when all details are already known, but these software’s are unable to do this in the early concept design phase when making design choices have the biggest impact. Therefore, an integrated simulation platform has been developed to predict wind turbine tonality, considering factors like gear mesh excitation and aero-acoustic masking, which is already applicable in the design concept phase when lots of design details are not known yet. This platform, linked to optimization software, allows ZF to proactively develop strategies to mitigate Noise, Vibration, and Harshness risks, resulting in cost-effective and harmonized solutions across their product platforms.

Design and realization of a pre-production platform for wind turbine manufacturing

Addressing the challenge of rehearsing large-scale equipment assembly, particularly for oversized components like wind turbine towers, hubs, nacelles, and blades, which often face quality issues such as substandard workmanship and wide tolerances during on-site assembly, a system has been developed for simulating wind turbine assembly. This system enables digital wind turbine assembly by creating virtual and production process models and employing intelligent database analysis. It resolves the problem of the absence of pre-production for large-scale equipment, meets the batch production needs of the wind turbine manufacturing industry, enhances the safety of wind turbine operations, improves operator assembly skills, and boosts production efficiency. This platform has already been implemented in the wind turbine manufacturing industry, yielding significant economic benefits.

A novel design of a hybrid glulam-steel substructure for the IEA 15-MW floating wind turbine

Wind energy has become increasingly recognised as a very promising type of renewable energy. In addition, floating offshore wind turbines have facilitated the development of electricity production in intermediate (45-150 m) and deep sea (>150 m) depths. Despite this, wind turbine manufacturing, installation, and operation may generate substantial greenhouse gas emissions. A novel hybrid glulam-steel floating substructure design is presented in this research, intended for the IEA 15 MW floating wind turbine. The objective is to contribute to advancing floating wind energy while minimising costs and carbon dioxide emissions. The objective of the novel design is to substitute steel with glued laminated lumber (glulam). It showcases an altered iteration of the UMaine VolturnUS-S semi-submersible platform originally created for the IEA 15 MW turbine. Before selecting one of three preliminary hybrid wood-steel models, the Ansys Workbench 2020 R1 is used to evaluate and appraise them per a set of criteria extracted from pertinent timber and steel standards. The chosen hybrid design conserves about 590 metric tonnes of steel mass compared to the UMaine VolturnUS-S semi-submersible platform. The selected model is then validated by executing a fully coupled aero-hydro-servo-elastic dynamic analysis with OpenFAST. Consideration is limited to the ultimate limit state design (ULS) for normal and severe operating situations. The utilisation factor of the glulam supporting structure for the IEA 15 MW turbine ranges from 74% to 94%, indicating that it is an effective load-bearing solution.

Carbon and Energy Life Cycle Analysis of Wind Energy Industry in Libya

By analyzing a wide range of energy, economic, and environmental variables for a variety of attractive locations in Libya, the study established the fundamentals of localizing the wind energy business in Libya. The estimate of the greenhouse gas (GHG) emission factor resulting from the conversion of wind energy into electric energy also includes the quantity of GHG emissions from cement manufacturing and transportation, as well as manufacturing (for various wind turbine manufacturers), sea transportation of wind energy equipment from the site of manufacture to the port of Tripoli, land transportation to the location of the wind energy farm, and calculating the energy and emissions used for recycling recyclable materials and for transportation. Hourly climate data over a 25-year period (1995-2020) were gathered from the SolarGis climate information portal. For many viable wind energy production locations in Libya, the System Advisor Model (SAM) software was used to calculate the productivity of wind farms with a 100 MW capacity. The study's findings showed that the Gamesa turbine, whose capital cost was around (146,916,400 dollars), had the best economic and environmental indices. The GHG emission rates for all the cities that were targeted ranged from 24-63g GHG/kWh. The time needed for carbon to recover ranged from 5.5 to 14.5 months. The expected energy payback time was 14 to 22 months. An LCOE's production costs ranged from 4.8 to 11.1 cents per kWh.

Soil–Structure Interactions for the Stability of Offshore Wind Foundations under Varying Weather Conditions

Fixed-bottom foundations of offshore structures, mainly monopiles, are subject to extreme events and other critical cyclic nature loads. Since offshore wind turbine structures are slender, the manufacturers of offshore wind turbines give a range of frequencies for safe operation during a structure’s life cycle. Highly reliable measurements and accurate determination of shear moduli and damping ratios are crucial to ensure the stability of these structures, for example, to avoid the resonance of the structures. Because foundation–soil properties change over a period of time due to various environmental factors, this should be taken into consideration for designs. In the current investigation, behaviours of dry sand under dynamic loads were explored. Cyclic loads of strain amplitudes of 0.05%, 0.1%, 0.25% and 0.5% were carried out in a cyclic simple shear apparatus to explore the evolution trend of the stiffness and damping ratio of the soil. Attempts were made to simulate varying weather conditions by conducting cyclic tests with different strain amplitudes representing normal weather conditions and extreme weather conditions. It was found that soil dynamic properties vary remarkably at first and then tend to stabilise under cyclic loading with the same strain amplitude. However, with varying strain amplitude, property variations continue further. From numerical analyses using the discrete element method, it was found that this is due to the disturbance of soil, causing further particle rearrangements and soil compactions, following a sudden change of strain amplitude, which leads to further property variations.

Reliability-Driven Multiechelon Inventory Optimization With Applications to Service Spare Parts for Wind Turbines

There are multiple warehouses in a multiechelon inventory system, and the size of the state space increases exponentially with the number of warehouses. Therefore, the curse of dimensionality becomes unavoidable when performing steady-state analysis. Most existing studies calculate the inventory cost or supply chain reliability based on specific assumptions. For example, it often assumes that the lead time is either zero or an integral multiple of the review period, and that each warehouse adopts a base-stock policy. This article considers a more practical and prevalent situation where the lead time is less than a review period, and a more general (s, S) strategy is adopted. The curse of dimensionality during steady-state analysis is alleviated by decomposing transition probabilities. Then, the cost and supply chain reliability are derived from steady-state distributions. Finally, a case study involving spare part inventory of wind turbines is considered. Nondominated inventory strategies are obtained using the particle swarm optimization method to strike a balance between costs for the wind turbine manufacturer and wind farm owners.

Beyond 15 MW: A cost of energy perspective on the next generation of drivetrain technologies for offshore wind turbines

Leading wind turbine manufacturers are racing to build larger and more powerful offshore machines. Drivetrain configurations often use a permanent-magnet synchronous generator (PMSG), in either a direct-drive configuration or coupled to a gearbox. With increasing demand for critical rare-earth magnets, new generator technologies are emerging to ensure a stable and secure supply chain. We evaluate three different topologies of radial flux synchronous generators employing high field magnets with reduced or no rare-earth content: a direct-drive interior PMSG (DD-IPMSG), a geared drivetrain combining a medium speed gearbox with a PMSG (MS-PMSG), and a direct-drive low-temperature superconducting generator (DD-LTSG). We develop a conceptual design module for each of these technologies within a larger framework for full turbine design. This provides the fairest comparison between technologies at nominal power ratings from 15–25MW, which represent the next generation of offshore wind turbines. The analyses show that if operational expenditures (OpEx) are constant across the technologies, MS-PMSG results in the lowest LCOE with reductions of up to 7% relative to DD-IPMSG. DD-LTSG also yields lower LCOE values by 2%–3% for fixed-bottom turbines and 3%–5% with a floating platform. However, results are sensitive to OpEx assumptions, with a mere 10% increase causing the conclusions to shift.

Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades

To cope with the increase in the manufacturing and operation of wind turbines, wind farm operators need inspection tools that are able to provide reliable information while keeping the downtime low. Current inspection techniques require the wind turbine to be stopped. This work presents the current progress in the project EvalTherm, in which passive thermography is evaluated as a possible non-destructive inspection tool for operational wind turbine blades (WTBs). A methodology to obtain thermal images of rotating WTBs has been established in this project. However, the quality of the results is heavily dependent on various aspects such as weather conditions, information on the inspected WTB, damage history, etc. In this work, a section of a used WTB is simulated using finite-element modelling (FEM) as well as experimentally tested for evaluating the accuracy of the model. Such a model will provide insight into the potential thermal response of a certain structure (with specific material properties) in given weather (boundary) conditions. The model is able to provide satisfactory predictions of the temporal thermal response of the structure, as well as indicate what thermal contrast(s) transients result from artificial defects introduced in the structure.

Data–Driven Wake Steering Control for a Simulated Wind Farm Model

Abstract: Upstream wind turbines yaw to divert their wakes away from downstream turbines, increasing the power produced. Nevertheless, the majority of wake steering techniques rely on offline lookup tables that translate a set of parameters, including wind speed and direction, to yaw angles for each turbine in a farm. These charts assume that every turbine is working well, however they may not be very accurate if one or more turbines are not producing their rated power due to low wind speed, malfunctions, scheduled maintenance, or emergency maintenance. This study provides an intelligent wake steering technique that, when calculating yaw angles, responds to the actual operating conditions of the turbine. A neural network is trained live to determine yaw angles from operating conditions, including turbine status, using a hybrid model and a learning-based method, i.e. an active control. The proposed control solution does not need to solve optimization problems for each combination of the turbines’ non-optimal working conditions in a farm; instead, the integration of learning strategy in the control design enables the creation of an active control scheme, in contrast to purely model-based approaches that use lookup tables provided by the wind turbine manufacturer or generated offline. The suggested methodology does not necessitate a substantial amount of training samples, unlike purely learning-based approaches like model-free reinforcement learning. In actuality, by taking use of the model during back propagation, the suggested approach learns more from each sample. Based on the flow redirection and induction in the steady state code, results are reported for both normal (nominal) wake steering with all turbines operating as well as defective conditions. It is a free tool for optimizing wind farms that The National Renewable Energy Laboratory (USA) offers. These yaw angles are contrasted and checked with those discovered through the resolution of an optimization issue. Active wake steering is made possible by the suggested solution, which employs a hybrid model and learning-based methodology, through sample efficient training and quick online evaluation. Finally, a hardware-in-the-loop test-bed is taken into consideration for assessing and confirming the performance of the suggested solutions in a more practical setting.