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Numerical simulation technology is a crucial tool for reducing costs and increasing efficiency in the wind power industry. However, with the development of large-scale wind turbines, the computational cost of numerical simulation has gradually increased. This paper uses the geometric similarity, structural similarity criterion, Reynolds similarity and boundary layer theory to establish a scaled model of the geometric three-dimensional shape, composite material, and finite element mesh of large wind turbine blades. The study analyzes the aerodynamic, gravitational, and centrifugal load variations within the scaled model. The proportional relationship between the scaled model's operating parameters, the numerical simulation's environmental parameters, and the mechanical response parameters is established. These parameters are coordinated to ensure the similarity of the blade structure and the fluid dynamics. For a geometric scale factor of 0.316, the relative difference in maximum deflection is 4.52%, with a reduction in calculation time by 48.1%. On the premise of ensuring the calculation accuracy of the aerodynamic and structural response of the blade, the calculation efficiency is effectively improved. [ABSTRACT FROM AUTHOR]

Purpose: Digital technologies open up unprecedented opportunities for the Chinese wind power industry to make rapid and comprehensive decisions. However, the relationship between digital technology adoption and radical and incremental innovations has not been empirically assessed. In addition, reconfiguration capability is the ability of firms to transform and respond to changes. How such an organizational capability influences the effectiveness of digital technology adoption is a black box. In response, this study aims to assess the relationship between digital technology adoption and radical and incremental innovations in the Chinese wind power industry and elucidate the moderating role of reconfiguration capability. Design/methodology/approach: Based on the data of listed companies in the Chinese wind power industry from 2006 to 2020, this study constructs regression models and validates the hypotheses. Findings: The correlation between digital technology adoption and incremental innovation in the wind power industry in China is significantly positive, but the relationship between digital technology adoption and radical innovation is not significant. In addition, reconfiguration capability significantly enhances the incentive effect of digital technology adoption on incremental innovation. Originality/value: To the best of the authors' knowledge, this study is one of the earliest to explore the heterogeneous relationships between digital technology adoption and radical and incremental innovations in emerging economies, advancing the theoretical insights into how digital transformation can foster different categories of technological innovations. Moreover, this study embeds dynamic capability theory into digital transformation research by exploring the boundary conditions for the effectiveness of digital technology adoption from the perspective of organizational dynamic capability, thereby expanding the boundaries of existing knowledge. [ABSTRACT FROM AUTHOR]

ABSTRACT A system for analysing steel plates is presented for an application in the wind power industry. The objective of the system is to assess the surface roughness as a preliminary step for the application of an anti‐corrosion coating. A number of noncontact sensor systems were considered, with the laser triangulation scanner proving to be the optimal solution. The samples are analysed in a test stand and the roughness is measured with this optical system. At the same time, the surface is recorded with a CMOS camera. An AI model is created from the sensor fusion of both systems, which can classify individual segments of the surface as well or poorly blasted. In the following step, the surface roughness is estimated as the Rz parameter by another AI model. An error of less than 6 μm is achieved. [ABSTRACT FROM AUTHOR]

Translation abstract Experimental investigations on the applicability of recycled carbon fibres in fibre‐reinforced concreteIn structural concrete, concretes reinforced with short fibres are mainly used in massive structural concrete components as well as in statically indeterminate components. These fibres also transfer tensile stresses after cracking. In Germany, the use of steel fibres is primarily regulated by the DAfStb guideline “Steel fibre reinforced concrete”. The international standard fib Model Code 2010 and the fib Bulletin 105 also permit the use of other fibre materials. In this work, the use of recycled carbon fibres as reinforcement in carbon fibre‐reinforced concrete (CFRC) is investigated in order to increase its load‐bearing capacity and ductility. Given the increasing proportion of carbon fibre reinforced polymers (CFRP) in the material cycle, particularly in the wind energy industry, this paper focuses on the reuse of CFRP waste. Two mixtures of recycled carbon fibres are investigated for their performance in fibre‐reinforced concrete with varying volume contents. Based on an analysis of the fibre mixtures, experimental investigations are carried out to determine values that describe the strength behaviour and fresh concrete properties of the CFRC. In three‐point flexural tensile tests, the fibre‐reinforced concrete with 2 % by volume can achieve an increase in flexural strength of +60 % compared to unreinforced concrete. The tests also show that the addition of carbon fibres impairs workability during the concreting process [ABSTRACT FROM AUTHOR]

The wind power industry (WPI), plays a crucial role in the reduction of global carbon emissions. Using SNA and the QAP model, this paper is aimed at investigating the impact mechanism of China's WPI innovation network from the perspective of multidimensional proximity while also summarising the trends in its evolution. The research has empirically demonstrated that the WPI innovation network has a progressively complex topology with an increase in network centrality and an increasing number of industry-university-research collaborations. The influence of multi-dimensional proximity on the evolution of China's WPI innovation network is significant, and the effect of proximity varies based on its type and stage. Moreover, technology leadership and policy support have emerged as critical driving forces for the development of the WPI innovation network. The effect of proximity provides a reference for countries to introduce the WPI. [ABSTRACT FROM AUTHOR]

As a renewable energy source, ocean wind energy plays an important role in addressing challenges such as global energy shortages and climate warming. In the past decade, the offshore wind power industry has developed rapidly. However, its development has also inevitably affected local social, economic and environmental aspects. Therefore, a timely understanding of offshore wind power dynamics development is crucial for its healthy and sustainable development. Based on this, this study designs and develops a more economical, reliable and real-time offshore wind turbine (OWT) extraction method by combining deep learning and the Google Earth Engine (GEE) cloud computing platform. The method consists of two main steps. The first part utilizes multiple semantic segmentation models to construct a multi-model detection method to initially detect OWTs. The second part utilizes the GEE cloud computing platform for installation time detection and secondary purification processing of the preliminary results. The results show that the number of global OWTs reached 13,609 by 2023, and the accuracy of the detection results reached 99.93%. China has been the fastest-growing country in offshore wind power in the last decade, from installing only 4 units in 2015 to installing 6,775 units in 2023 and surpassing the UK in 2020 and becoming the country building the most OWTs worldwide. Currently, 85% of the world's OWTs are located in China and European North Sea waters. Additionally, other regions have great potential for offshore wind development. Finally, this study provides the world's most up-to-date and complete OWT dataset, which can provide data support for research on marine ecological and environmental protection, marine spatial planning, and socioeconomic benefits. [ABSTRACT FROM AUTHOR]

The wind energy industry is witnessing a new era of extraordinary growth as the demand for renewable energy continues to grow. However, accurately predicting wind speed remains a significant challenge due to its high fluctuation and randomness. These difficulties hinder effective wind farm management and integration into the power grid. To address this issue, we propose the MRGS-LSTM model to improve the accuracy and reliability of wind speed prediction results, which considers the complex spatio-temporal correlations between features at multiple sites. First, mRMR-RF filters the input multidimensional meteorological variables and computes the feature subset with minimum information redundancy. Second, the feature map topology is constructed by quantifying the spatial distance distribution of the multiple sites and the maximum mutual information coefficient among the features. On this basis, the GraphSAGE framework is used to sample and aggregate the feature information of neighboring sites to extract spatial feature vectors. Then, the spatial feature vectors are input into the long short-term memory (LSTM) model after sliding window sampling. The LSTM model learns the temporal features of wind speed data to output the predicted results of the spatio-temporal correlation at each site. Finally, through the simulation experiments based on real historical data from the Roscoe Wind Farm in Texas, United States, we prove that our model MRGS-LSTM improves the performance of MAE by 15.43%-27.97% and RMSE by 12.57%-25.40% compared with other models of the same type. The experimental results verify the validity and superiority of our proposed model and provide a more reliable basis for the scheduling and optimization of wind farms. [ABSTRACT FROM AUTHOR]

The world is undergoing profound changes in energy and technology. Countries are vigorously developing new sustainable energy sources and technologies. Renewable energy sources encompass various technologies such as wind turbines, solar energy, nuclear energy, and bioenergy. Additionally, emerging technology fields include new energy vehicles, robots, and artificial intelligence devices, among others. The renewable energy industries and implementation of new technologies necessitate the development and adoption of new equipment and components. Austempered ductile iron (ADI) is renowned for its unique microstructure and superior properties. By utilizing ADI, lightweight and innovative castings can be designed to not only reduce weight but also save energy and decrease emissions. More importantly, these castings enhance the efficiency and reliability of new energy equipment and emerging technology installations. This paper describes the development, applications, and future prospects of lightweight and innovative ADI castings within sectors such as solar photovoltaic (PV), wind power generation, industry robots, and trucks in China. [ABSTRACT FROM AUTHOR]

Wind turbine blades are primarily composed of fiberglass composite, posing a significant recycling challenge for the wind energy industry. This paper introduces a novel recycling approach by comprehensively analyzing the pozzolanic reactivity of recycled powder as a new supplementary cementitious material (SCM). A systematic characterization using laboratory techniques is first described, establishing both the chemical and morphological properties of the powder and suggesting that the material was likely to be capable of acting as a pozzolan. The effects of thermal and mechanical processing on the reactivity characteristics of the material were elucidated using a suite of analytical and standardized characterization approaches. It was found that through heat treatment to remove impinging resin and subsequent mechanical processing to synthesize a fine powder, the reactivity of the material could be improved to an extent at which the performance characteristics of a conventional class F fly ash were closely matched. For instance, mortar containing 10% of thermally-mechanically processed powder achieves 95% of the 28-day strength of cement mortar. This paper opens the door for both the use of these materials to bolster dwindling supplies of supplementary cementitious materials, and to provide a much-needed reprocessing route for waste fiberglass which are otherwise highly challenging to dispose of cost-effectively. [ABSTRACT FROM AUTHOR]

In view of the fact that dynamic stall models in the wind energy industry such as ONERA model, Beddoes–Leishman model, and Snel model are mostly semi‐empirical models, and the determination of empirical time constants has a great influence on the model accuracy. To optimize the time constant in dynamic stall model and improve the prediction accuracy of unsteady aerodynamics, the influence of boundary layer and pressure lag on the unsteady performance of the S809 airfoil under 2D flow conditions is explored using a simple semi‐empirical dynamic stall engineering model. The proposed model consists of four first‐order differential equations accounting for attached flow and dynamic separation flow of trailing edge based on the Theodorsen theory. A validation is carried out by the wind tunnel experiment in the Key Laboratory of Wind and Solar Energy Utilization Technology of the Ministry of Education at Inner Mongolia University of Technology. The main conclusions are as follows. The time constants for lag in pressure and boundary layer both have a great influence on the unsteady lift coefficient. When the mean angle of attack is relatively small and the airflow is between the attached flow and the separated flow, appropriately reducing the time constant can make the prediction results closer to the experimental values. When the mean angle of attack is relatively large and the airflow is in condition of fully separated flow, the time constant value can be appropriately increased. The influence of pressure lag and boundary layer lag on the unsteady drag coefficient is not significant. [ABSTRACT FROM AUTHOR]

A significant number of first-generation offshore wind turbines (OWTs) have either reached or are approaching the end of their operational lifespan and need to be upgraded or replaced with more modern units. In response to this concern, governments, regulatory bodies and industries have initiated the development of effective end-of-life (EOL) management strategies for offshore wind infrastructure. Lifetime extension is a relatively new concept that has recently gained significant attention within the offshore wind energy community. Extending the service lifetime of OWTs can yield many benefits, such as reduced capital cost, increased return on investment (ROI), improved overall energy output, and reduced toxic gas emissions. Nevertheless, it is important to identify and prepare for the challenges that may limit the full exploitation of the potential for OWT lifetime extension projects. The objective of this paper is to present a detailed PESTLE analysis to evaluate the various political, economic, sociological, technological, legal, and environmental challenges that must be overcome to successfully implement lifetime extension projects in the offshore wind energy sector. We propose a decision framework for extending the lifetime of OWTs, involving the degradation mechanisms and failure modes of components, remaining useful life estimation processes, safety and structural integrity assessments, economic and environmental evaluations, and the selection of lifetime extension technologies among remanufacturing, retrofitting, and reconditioning. Finally, we outline some of the opportunities that lifetime extension can offer for the wind energy industry to foster a more circular and sustainable economy in the future. [ABSTRACT FROM AUTHOR]

High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, wind resource development has important practical significance for alleviating environmental pollution problems in China. As China's clean energy province and western economic center, Sichuan's wind power industry is gradually starting from the 13th Five-Year Plan. Considering the volatility and periodic characteristics of wind power generation in Sichuan Province, this paper proposes an optimized seasonal grey model based on Aquila Optimizer. The proposed model selects dummy variables 1 and 0 to represent seasonal factors and perform seasonal classification of the sample data. According to the classification sequence, this paper constructs the grey forecasting model with optimized initial and background values by Aquila Optimizer. The proposed model predicts wind power generation in Sichuan Province and verifies its validity and rationality by comparing results with other selected methods. In training and test groups, the performance results of the proposed model are better. The mean absolute percentage error is 3.44% and 12.34%, and the root mean square error is 0.86% and 4.33%. Finally, this paper further provides policy advice and planning based on the prediction results for the future development of Sichuan Province's clean energy industry during the 14th Five-Year Plan period. [ABSTRACT FROM AUTHOR]

As a predatory fish that migrates between freshwater and marine environments, the sea trout (Salmo trutta) is important in linking these systems. This study investigated movement patterns of sea trout in a coastal fjord at the Swedish Skagerrak region from August 2018 to January 2019, using acoustic telemetry, while assessing these against environmental variables across different spatial and temporal scales. Six acoustic receivers were deployed in the fjord and a river, which flows into the upper reaches of the fjord, with the aim of detecting 20 sea trout that had been tagged with acoustic transmitters. Sea surface temperature and winds (east–west) affected movement patterns of the sea trout the most, while changes in atmospheric pressure were also important, but to a lesser extent. Sea surface temperature and atmospheric pressure both had a positive relationship with the number of detections, whereas stronger winds from the east (i.e. from land) resulted in more detections than stronger winds from the west (i.e. from the ocean). In addition, interesting diel (day–night) movement patterns were observed for some fish. A significant positive correlation was also discovered between the weight of the fish and the number of detections. This study offers insight in movements of sea trout that use coastal habitats and how environmental conditions can affect movement patterns in a fjord system. To further our understanding of sea trout movement patterns and connectivity, tracking from river, through fjord, out to sea and at a longer time scale with more variation in fish size would be valuable to understand more about the complex movement dynamics of this important species. [ABSTRACT FROM AUTHOR]

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Nowadays, the wind power market is growing rapidly, while the cost of wind power equipment is decreasing, so Vietnam is currently building many wind power projects to ensure green energy development in its power system. However, some barriers in price mechanisms, and economic and technical conditions have also caused disadvantages in the process of developing wind power projects. This paper studies the SWOT-TOWS analysis to evaluate in greater detail the strengths, weaknesses, opportunities, and threat factors linked to it. Then the former compares the internal and external factors influencing the wind power industry on the way it exploits potential strategies. In general, Vietnam has satisfactory wind power development potential, and the wind power sector has been supported by a number of strong but unstable policies in the past. The rapid development of wind power capacity in recent times has also led to great challenges for investors and managers in actual operating conditions. Currently, investment costs for wind power plants are still quite high, Feed in Tariff (FIT) prices are not stable, transmission grid capacity is limited, and environmental treatment issues during construction and operation have not been fully considered. [ABSTRACT FROM AUTHOR]

The introduction of thousands of wind turbines along the North American Atlantic continental shelf over the next decade will constitute the largest regional change in marine substrates since the retreat of the Laurentide Ice Sheet over 14,000 years ago. Here, two large data sets, SMAST drop camera survey (242,949 samples, 2003 to 2019) and the US Geological Survey databases (27,784 samples, 1966 to 2011), are combined to derive sea floor surficial substrate probability maps for the Northeastern US continental shelf from Virginia Beach to the Gulf of Maine to 300 m depth (218,571 km2). Geostatistical models were used to estimate the probability of five geologic and one biogenic substrate types being present at a 250 m resolution, and the proportional contribution of each substrate type to the seabed composition at a 500 m resolution. By providing the first synoptic maps depicting the probability of a particular substrate or combination of substrates occurring at any location on the Northeastern US continental shelf, including planned wind energy sites, we aim to (1) provide insights regarding how substrates in the areas selected for wind energy development compare with other locations, (2) motivate the development of a priori expectations for ecosystem changes to inform monitoring and research efforts going forward, and (3) to provide a baseline characterization of the Northeastern US continental shelf surficial substrates to support robust examination of the future changes observed in areas impacted by wind energy installations. [ABSTRACT FROM AUTHOR]

We consider the scheduling of battery charging of electric vehicles (EVs) integrated with renewable power generation. The increasing adoption of EVs and the development of renewable energies contribute importance to this research. The optimization of charging scheduling is challenging because of the large action space, the multi-stage decision making, and the high uncertainty. To solve this problem is time-consuming when the scale of the system is large. It is urgent to develop a practical and efficient method to properly schedule the charging of EVs. The contribution of this work is threefold. First, we provide a sufficient condition on which the charging of EVs can be completely self-sustained by distributed generation. An algorithm is proposed to obtain the optimal charging policy when the sufficient condition holds. Second, the scenario when the supply of the renewable power generation is deficient is investigated. We prove that when the renewable generation is deterministic there exists an optimal policy which follows the modified least laxity and longer remaining processing time first (mLLLP) rule. Third, we provide an adaptive rule-based algorithm which obtains a near-optimal charging policy efficiently in general situations. We test the proposed algorithm by numerical experiments. The results show that it performs better than the other existing rule-based methods. [ABSTRACT FROM AUTHOR]

The urgent requirement for efficient recycling strategies in the wind energy industry prompted this study to explore the behavior of methanesulfonic acid (MSA) in the solvolysis of carbon fiber‐reinforced plastics (CFRP), as an alternative to standard solvents and acids. For the investigation, two layers of carbon fibers, infused with amine‐based epoxy through a vacuum‐assisted resin infusion process, were applied. The results showed that MSA was the most effective solvent for the solvolysis of CFRP, compared to other investigated common acids. The recycled products demonstrated satisfactory properties for both the matrix and fiber, which were comparable to those of the virgin materials. [ABSTRACT FROM AUTHOR]

Offshore wind turbines have rapidly scaled up in recent years, with plans to construct turbines up to 22 MW in the next decade. However, the operations and maintenance (O&M) requirements for these 'next‐generation turbines' remain largely unknown. In this study, the total O&M costs are calculated, using a bench‐marked O&M model, for a hypothetical 10 MW turbine scenario using two drive train configurations, based on known failure rates of smaller turbines. The O&M costs of the 10 MW turbines are compared with those of existing 3 MW turbines in two case studies: a North Sea wind farm and an East Coast US wind farm. Overall, direct drive 10 MW turbines performed better depending on the site's climate conditions. The study indicated that the two‐stage drive train configuration may be more suitable for the US site than the North Sea, depending on the turbine's failure rate. The US site benefited from increased availability due to more favourable weather windows, resulting in lower lost revenue for the two‐stage configuration despite high transport costs. The study found that the failure rate of 10 MW offshore wind turbines in the North Sea with a two‐stage gearbox can increase by as much as 30% compared to the 3 MW failure rates without increasing direct O&M costs. These findings are crucial for the offshore wind energy industry, particularly for OEMs, developers and maintenance providers, as they provide insights into the required reliability for next generation turbines to reduce O&M costs compared to existing 3 MW turbines. [ABSTRACT FROM AUTHOR]

This document is a list of references for various research articles related to renewable energy, sustainability, and economic development. The articles cover topics such as the feasibility of renewable energy in different countries, the role of circular economy practices in sustainable development, the analysis of energy generation and consumption patterns, and the potential benefits of renewable energy sources. The document also acknowledges the funding received for the research and the co-financing of the journal by the Ministry of Education and Science of the Republic of Poland. [Extracted from the article]

The increasing adoption of robotic solutions for inspection tasks in challenging environments is becoming increasingly prevalent, particularly in the offshore wind energy industry. This trend is driven by the critical need to safeguard the integrity and operational efficiency of offshore infrastructure. Consequently, the design of inspection vehicles must comply with rigorous requirements established by the offshore Operation and Maintenance (O&M) industry. This work presents the design of an autonomous surface vehicle (ASV), named Nautilus, specifically tailored to withstand the demanding conditions of offshore O&M scenarios. The design encompasses both hardware and software architectures, ensuring Nautilus's robustness and adaptability to the harsh maritime environment. It presents a compact hull capable of operating in moderate sea states (wave height up to 2.5 m), with a modular hardware and software architecture that is easily adapted to the mission requirements. It has a perception payload and communication system for edge and real‐time computing, communicates with a Shore Control Center and allows beyond visual line‐of‐sight operations. The Nautilus software architecture aims to provide the necessary flexibility for different mission requirements to offer a unified software architecture for O&M operations. Nautilus's capabilities were validated through the professional testing process of the ATLANTIS Test Center, involving operations in both near‐real and real‐world environments. This validation process culminated in Nautilus's reaching a Technology Readiness Level 8 and became the first ASV to execute autonomous tasks at a floating offshore wind farm located in the Atlantic. [ABSTRACT FROM AUTHOR]

Monopile foundations are extensively utilized in the rapidly expanding offshore wind power industry, and the stability of these foundations has become a crucial factor for ensuring the safety of offshore wind power projects. Such foundations are subjected to a myriad of complex environmental loads during their operational lifespan. Whilst current research predominantly concentrates on the effects of wind, wave, and current loads on monopile stability in extreme environments, it is imperative to consider the potential influence of unexpected submarine landslide loads. In this study, we provide a comprehensive overview of wind, wave, current, and submarine landslide loads on monopile foundations in extreme environments. Subsequently, we establish a finite element model for analyzing the stability of monopiles under complex lateral loads, and validate the accuracy of the model by comparing it with the previous numerical findings. A case study is performed with reference to the Xiangshui Wind Farm project to analyze the effects of varying submarine landslide densities, velocities, impact heights, and seabed sediment strengths on pile head horizontal displacement, pile rotation at the mudline, and maximum bending moment. The findings indicate that the increase in submarine landslide density, velocity, and impact height leads to an increase in horizontal displacement at the pile head, pile rotation at the mudline, and maximum bending moments, and a horizontal failure mode is observed in seabed sediments. Furthermore, under the same load conditions, a decrease in seabed sediment strength and internal friction angle triggers instability in monopiles, with a noteworthy transition from horizontal failure to deep-seated seabed sediment failure. Finally, we propose a criterion for monopile instability under diverse loading conditions. [ABSTRACT FROM AUTHOR]

This paper shows that collaborative innovation projects (CIPs) are an important arena for both knowledge generation and its incorporation into the industrial knowledge base (IKB). By differentiating between the cultural-cognitive, normative, and regulative dimensions of technology generation and diffusion, we describe interdependencies between CIPs and IKBs. On the basis of three vignettes from the German wind energy industry, six interrelations (translation, imitation, structuring devices, consolidation, strategic closure, and strategic inertia) are identified on how CIPs contribute to IKBs. [ABSTRACT FROM AUTHOR]

AbstractThis paper proposes a new testing method, phased array ultrasonic testing, for the internal defects of gear teeth, which can be used to inspect the teeth of final products, breaking the limitations of incomplete volume coverage of conventional ultrasonic testing. This paper mainly discusses the inspection process of phased array ultrasonic testing, and verifies the feasibility of phased array ultrasonic testing for gear teeth defects of finished products by using physical and chemical inspection technology. The practical application results show that the phased array ultrasonic testing technology uses sector scanning mode to scan the area comprehensively between the pitch circle and the base circle, and the inspection image displayed by the equipment is intuitive, which can clearly identify defects. The number of defects inspected by phased array ultrasonic testing is consistent with the results of the physical and chemical inspection technology. The above summary shows that phased array ultrasonic testing is feasible, and the test results are reliable.

Carbon fiber reinforced polymer (CFRP) composites are popular materials in the aerospace and automotive industries because of their low weight, high strength, and corrosion resistance. However, wrinkles or geometric distortions in the composite layers significantly reduce their mechanical performance and structural integrity. This paper presents a method for non-destructively extracting the three-dimensional geometry, lamina by lamina, of a laminated composite. A method is introduced for fabricating consistent out-of-plane wrinkled CFRP laminate panels, simulating the in-service wrinkle observed in industries that utilize thick structure composites such as the vertical lift or wind power industries. The individual lamina geometries are extracted from the fabricated coupon with an embedded wrinkle from captured ultrasonic waveforms generated from single-element conventional ultrasonic (UT) scan data. From the extracted waveforms, a method is presented to characterize the wrinkle features within each individual lamina, specifically the spatially varying wrinkle height and intensity for the wrinkle. Parts were fabricated with visibly undetectable wrinkles using a wet layup process and a hot press for curing. Scans were performed in a conventional immersion tank scanning system, and the scan data were analyzed for wrinkle detection and characterization. Extraction of the layers was performed based on tracking the voltage peaks from A-scans in the time domain. Spatial Gaussian averaging was performed to smooth the A-scans, from which the surfaces were extracted for each individual lamina. The extracted winkle surface aligned with the anticipated wrinkle geometry, and a single parameter for quantification of the wrinkle intensity for each lamina is presented. [ABSTRACT FROM AUTHOR]

Clean energy transformation in major powers, especially the rapidly expanding electric vehicle and wind power industries, has sparked an increasing demand for strategic resources such as rare earths (RE). The RE industrial chain has become a focal area of geopolitical competition between China and the United States. This paper utilizes theories and methods from law and political economics, employing the classic paradigm of global governance, to examine the underlying motivations and geopolitical impacts of the United States in promoting the restructuring of the global rare earth industrial chain. Taking into account the two major characteristics of the U.S.' geopolitical strategy, namely 'controlling key industrial chains' and 'containing China with allies,' this paper reveals the underlying logic and strategic responses of significant political and economic relationships in the ongoing geopolitical competition. These relationships include the connection between the decoupling of the RE industrial chain and reconstruction of the global 'dual chain' pattern, the enactment of the 'three major acts' by the U.S., and the dominance of the global clean energy industry system, as well as the game between China and the United States as major powers and Japan's industrial security. The results show that: (1) In terms of controlling key industrial chains, the technological 'de-rare earth' initiatives of downstream enterprises are reinforcing the 'de-sinicization' strategic orientation of western governments, and vice versa. This joint effort is promoting the formation of a global strategic resource 'dual chain' pattern. (2) In terms of containing China with allies, the United States requires that Japan and other allied countries share the responsibility in geopolitical competition with China. Japan, driven by its own interests, has been deeply involved in the restructuring of the global RE industrial chain, shifting from a high dependence on Chinese RE imports to a deep participation in a new global RE industrial chain led by the U.S. (3) The promulgation of the 'three major acts' by the U S. is a strong proof of its consistent use of domestic laws to shape geopolitical relations. The underlying motivation behind this is to reshape the strategic resource industrial chain and gain control of the global clean energy transformation. In the face of escalating strategic resource competition and based upon the 'dual circulation' new development pattern, China should, on the one hand, leverage its resources and production capacity advantages in the front and middle streams of the industrial chains, leading the independent extension of the strategic resource industry chain through innovation. On the other hand, China should engage strategically and integrate global key mineral resources, develop effective countermeasures, and continuously enhance the resilience of key industrial chains such as rare earths, so as to improve the level of national strategic resource security. [ABSTRACT FROM AUTHOR]

The Chinese government has strongly acknowledged the strategic significance of offshore wind power in hydrogen production and has introduced many relevant policies for promoting the offshore wind power industry development. This study explains the evolution of policies regarding Chinese offshore wind power industry since 1995, with evolutionary characteristics such as emphasis on government role change, focus on problem orientation, prioritizing industrial upgrading, and close link to national energy strategy. However, there are still challenges in the formulation and implementation of policies, including the lack of scientific industrial construction planning, insufficient incentives for technological innovation, imperfect support for industrial integration, and inadequate environmental regulation. Moreover, this study also proposes prospects for the improvement and implementation of offshore wind power industry policies in China. The results of the study are intended to provide insights for decision makers in the clean energy industry and a useful reference for future hydrogen energy development. • This study offers a panorama of China's offshore wind power industry policy. • China's offshore wind power industry policy has distinct evolution characteristics. • This study analyzes the prospects of China's offshore wind power industry policy. • Results provide reference for the offshore wind power hydrogen production policy. [ABSTRACT FROM AUTHOR]

The modelling and analysis of high‐frequency bearing voltage are of great significance to the assessment and mitigation of the electrical erosion risk in wind power systems. However, the dual‐winding permanent magnet synchronous generator (DW‐PMSG), as one of the mainstream models in wind power industry, has not been specifically analysed for its bearing voltage modelling method in the existing research. The high frequency common mode equivalent circuit model of DW‐PMSG is established, and the effect of parasitic parameters between two sets of winding on bearing voltage is analysed. A model parameters extraction method based on differential evolution algorithm is proposed, and the range of parameters is estimated by finite element simulation and test results, which improves the search efficiency and solution accuracy. The accuracy of the proposed model is verified by the comparison of simulation and experimental results. On this basis, it is possible to conduct more in‐depth research on the bearing voltage and bearing currents of DW‐PMSG, and provide theoretical basis and simulation means for the design of suppression schemes. [ABSTRACT FROM AUTHOR]

In recent years, the vigorous development of the wind power industry has become an important measure in the transformation of energy structure in China. However, the overall low technical efficiency of wind farms has severely hindered wind power industrial development. It is of great practical significance to evaluate the technical efficiency (TE) of wind power in China and analyze its main factors. Most of the existing literature on the assessment of the TE of wind power in China focuses only on large listed companies and applies the traditional data envelopment analysis (DEA) while ignoring its potential shortcomings for TE estimation. Based on panel data, this paper used stochastic frontier analysis (SFA) to construct an analytical model for assessing the TE and influencing factors of Chinese wind farms and compared the results with those from DEA to verify the robustness. The empirical results showed that the TE of Chinese wind farms was generally low. The age of a wind farm and its power consumption have a negative impact on its technical efficiency, while the utilization of power generation equipment has a positive impact on its technical efficiency. Enhancing the technological innovation capabilities of wind power companies, speeding up the construction of supporting infrastructure and solving structural problems of wind power supply and demand are important measures for the wind power industry to improve the overall TE and promote industrial development in China. [ABSTRACT FROM AUTHOR]

In the context of the "dual carbon" strategy, how to leverage green finance to promote China's wind power industry is a hot topic. Unlike existing literature, this article uses a nonparametric additive model to investigate the impact and mechanism of green finance on wind power development. Research has found that green finance has an inverted U-shaped nonlinear impact on wind power development, indicating that green finance has a more prominent contribution to the wind power industry in the early stages. Further mechanism research indicates that green finance affects the wind power industry through foreign direct investment and green technology innovation. Specifically, with the relaxation of foreign direct investment conditions in the energy sector, the role of foreign direct investment in promoting the wind power industrymore prominent in the later stages. In the early stages, government support was greater, and green technology patents grew rapidly, driving green technology innovation to have a more significant impact on the wind power industry. In addition, the impact of fiscal decentralization, wind power prices, and environmental regulations on the wind power industry also exhibits significant nonlinear characteristics. This article helps to comprehensively understand themechanismand impact of green finance on wind power development, and provides a reliable basis for optimizing green finance policy and effectively promoting wind power. [ABSTRACT FROM AUTHOR]

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)--key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO2 forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections. [ABSTRACT FROM AUTHOR]

European petroleum majors have moved into offshore windfarm projects, with large investments and ambitious capacity and production targets. In aggressive bidding for Contracts for Difference in the UK, where oil companies have played a key part, we have seen the inflation-adjusted strike price fall 65% from 2015 to 2019. Researchers question whether LCOE will fall to the same extent and would like to see more research on the economic return of the companies making offshore wind investment. We address this by a transparent project economics analysis of the UK bottom-fixed Dogger Bank project. It is the largest offshore windfarm project in the world under development and the UK is the country with highest offshore wind capacity. The project is owned by Equinor, SSE Renewables and ENI. Our analysis shows that the project is expected to be unprofitable. Several of the input variables, however, are subject to considerable estimation uncertainty. We also present a low case and a high case scenario. Decomposition of the high case reveals factors that can contribute to a profitable wind power industry. We discuss financial issues facing oil company investment portfolios combining low return/ low risk renewables and high return/high risk petroleum. Offshore windfarms are organised as special purpose vehicle (SPV) companies. We analyse the economic interactions between the SPVs and the oil companies, and address accounting and financial issues. [ABSTRACT FROM AUTHOR]

The foundation of an offshore wind turbine (OWT) accounts for up to 20% of the total cost; therefore, investigations into reliable and efficient foundations are important for the offshore wind energy industry. This article describes an innovative winged caisson foundation for OWTs, which adapts the conventional caisson foundation to produce higher overturning capacities. The behaviour of this proposed novel foundation in the sand was investigated through experimental and numerical modelling using a series of 1 g tests (1/70th scale), centrifuge model tests (70 g ), and finite element (FE) simulations. Models with various wing sizes installed in different sand densities were tested in the laboratory by applying an overturning load. In this article, the moment–rotation performance of the foundation under monotonic loading is compared against that of conventional caissons to assess the potential benefits of adding wings to caisson foundations. Results show that there is a significant increase in overturning capacity provided by the novel foundation. FE models were first validated against experimental results, then, used to conduct a parametric study to better understand the behaviour of the winged caissons beyond the scaled model tests. In addition, the FE models were used to evaluate the drained response of the proposed foundation under combined loading. [ABSTRACT FROM AUTHOR]

The growing interest in floating offshore wind turbines (FOWTs) is rooted in the potential source of increased offshore energy production. As the technology is still in a pre-industrial state, several questions remain to be addressed where little field data are available. This study uses physical modelling at a reduced scale to investigate the signature of the floating motions into the wake spectral content of a simplified FOWT model. A wind turbine model based on the actuator disc concept is placed in an atmospheric boundary layer wind tunnel and subjected to a range of surge, heave and pitch motions. The signatures of idealised sinusoidal motion and realistic broadband motion on the model's wake at distances of 4.6 D (D being the disc diameter) and 8 D are measured through the use of a rake of single hot wires. The spectral analysis shows that harmonic motion leaves clear signatures in the far wake's energy spectra, mainly in the top tip region, while broadband motion does not leave easily detectable signatures. [ABSTRACT FROM AUTHOR]

The High Voltage Direct Current (HVDC) transmission technology employing modular multilevel converters (MMCs) can effectively enhance the transmission efficiency and stability of offshore wind farms, thereby aiding the promotion of large−scale utilization of new energy. This holds significant importance for achieving the dual carbon goals. Aiming at the problem of negative sequence current circulation in MMC−HVDC transmission systems, a circulation suppression strategy based on augmented order decoupling linear active disturbance rejection control (LADRC) is proposed in this paper. By introducing new state variables into the traditional ADRC structure, the actual output deviation signal and observation gain signal from the disturbance observation value of the system are used. It can not only realize the decoupling control of disturbance and tracking terms but also enhance the disturbance immunity, robustness and rapidity of the controller. Finally, an 18−level MMC system model is built based on Matlab (9.12.0.1884302 (R2022a)) & Simulink (R2022a), and the circulation suppression effects of stable operation and voltage sudden change are simulated and compared, which verifies the suppression effect of the improved control strategy on negative sequence current circulation, which lays a theoretical and application foundation for the sustainable development of the offshore wind power industry. [ABSTRACT FROM AUTHOR]

Purpose: Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation. Design/methodology/approach: Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses. Findings: The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs. Originality/value: This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms. [ABSTRACT FROM AUTHOR]

With the advancement of China's wind power industry, research into full-scale structural testing of wind turbine blades, including static testing and fatigue testing, has shown increasing significance. Static testing measures the deflection at fixed points, using pull-wire sensors in industrial practice. However, the demerits of this method involve single dimension, excessive deviation, costly experiment, and complex installment. Given the advantages that lidar provides, correspondingly, high data density, precision, and convenience, we proposed a simple and efficient spatial large deflection measurement system for wind turbine blades with multi lidars. For point clouds collected from lidar scanners, registration based on point primitives and geometric primitives, dynamic radius DBSCAN clustering, spatial line clustering, and line integrals are applied to calculate the 3D coordinates of measured points on the blade. Experimentally validated, the proposed method demonstrates its effectiveness in serving as a viable alternative to the traditional pull-wire sensor measurement approach. In the minimum oscillation direction test, the measurement error is controlled within 3% compared to the theoretical value. Simultaneously, in the maximum swing direction test, the 3D coordinates of the measured point remain consistent with the changing trend observed under small deformation. These results confirm the feasibility of the system and its potentials to be generalized. [ABSTRACT FROM AUTHOR]

In pursuit of China's goals for carbon peak and carbon neutrality, wind turbines are continually evolving to achieve a lower levelized cost of energy. The primary technological focus in the wind power industry is on large-scale, lightweight designs for entire turbines to enhance cost competitiveness. However, this advancement has led to an increased risk of blade fractures under extreme operating conditions. This paper addresses this challenging issue by using geometrically exact beam theory to develop a nonlinear simulation model for long, flexible blades. The model accounts for sudden changes in blade properties at the moment of failure, covering both the extensive motions and deformations of the fractured blade. The validation of the proposed model is carried out by comparing the results from power production cases with bladed simulations and further validating the simulations of blade fracture load cases against measurement data. The methodologies and findings presented in this study offer valuable insights for diagnosing faults in wind turbines. [ABSTRACT FROM AUTHOR]

As the use of wind energy expands worldwide, the wind energy industry is considering building larger clusters of turbines. Existing computational methods to design and optimize the layout of wind farms are well suited for medium-sized plants; however, these approaches need to be improved to ensure efficient scaling to large wind farms. This work investigates strategies for covering this gap, focusing on gradient-based (GB) approaches. We investigated the main bottlenecks of the problem, including the computational time per iteration, multi-start for GB optimization, and the number of iterations to achieve convergence. The open-source tools PyWake and TOPFARM were used to carry out the numerical experiments. The results show algorithmic differentiation (AD) as an effective strategy for reducing the time per iteration. The speedup reached by AD scales linearly with the number of wind turbines, reaching 75 times for a wind farm with 500 wind turbines. However, memory requirements may make AD unfeasible on personal computers or for larger farms. Moreover, flow case parallelization was found to reduce the time per iteration, but the speedup remains roughly constant with the number of wind turbines. Therefore, top-level parallelization of each multi-start was found to be a more efficient approach for GB optimization. The handling of spacing constraints was found to dominate the iteration time for large wind farms. In this study, we ran the optimizations without spacing constraints and observed that all wind turbines were separated by at least 1.4 D. The number of iterations until convergence was found to scale linearly with the number of wind turbines by a factor of 2.3, but further investigation is necessary for generalizations. Furthermore, we have found that initializing the layouts using a heuristic approach called Smart-Start (SMAST) significantly reduced the number of multi-starts during GB optimization. Running only one optimization for a wind farm with 279 turbines initialized with SMAST resulted in a higher final annual energy production (AEP) than 5000 optimizations initialized with random layouts. Finally, estimates for the total time reduction were made assuming that the trends found in this work for the time per iteration, number of iterations, and number of multi-starts hold for larger wind farms. One optimization of a wind farm with 500 wind turbines combining SMAST, AD, and flow case parallelization and without spacing constraints takes 15.6 h, whereas 5000 optimizations with random initial layouts, finite differences, spacing constraints, and top-level parallelization are expected to take around 300 years. [ABSTRACT FROM AUTHOR]

The increasing prominence of glass-fibre-reinforced plastics (GFRPs) in the wind energy industry, due to their exceptional combination of strength, low weight, and resistance to corrosion, makes them an ideal candidate for enhancing the performance and durability of wind turbine blades. The unique properties of GFRPs not only contribute to reduced energy costs through improved aerodynamic efficiency but also extend the operational lifespan of wind turbines. By modifying the epoxy resin with carbon nanofillers, an even higher degree of performance can be achieved. In this work, graphene nanoplatelet (GNP)-enhanced GFRPs are produced through industrial methods (filament winding) and coupons are extracted and tested for their mechanical performance after harsh environmental aging in high temperature and moisture. GNPs enhance the in-plane shear strength of GFRP by 200%, while reducing their water uptake by as much as 40%. [ABSTRACT FROM AUTHOR]

• MADRL is used to solve large scale multi-echelon inventory optimization problem. • VDTD3 is developed by embedding TD3 in value decomposition method. • Multi-echelon inventory optimization problem is formulated by Dec-POMDP. • Shared actor networks are customised to process heterogeneous subsystems. • Domain knowledge is combined in RL via experience buffer modification. Multi-echelon inventory systems are commonly used in practice to satisfy widely distributed random demands of spare parts in an efficient and cost-effective manner. Optimization of a multi-echelon inventory system is a decision-making problem under uncertainties. Classic inventory policies (e.g. (s, S) and (R, Q)) that do not consider the inventory positions of other warehouses become suboptimal due to interrelationships among different warehouses caused by transshipment. The Markov decision process (MDP) is an effective tool for inventory optimization, which does not require a predetermined parameterized policy structure. Unfortunately, both the state and action spaces of MDP suffer from the curse of dimensionality when the number of warehouses increases. This paper optimizes the inventory of a large-scale multi-echelon inventory system using a new multi-agent deep reinforcement learning (MADRL) algorithm named EM-VDTD3 that is developed by introducing value decomposition and experience buffer modification into the twin delayed deep deterministic policy gradient (TD3) algorithm. Each agent in EM-VDTD3 manages a subsystem in the multi-echelon inventory system. Because different agents share the same network parameters, networks are customized to process subsystems with different parameters. Domain knowledge of inventory control is embedded in the learning process of EM-VDTD3 by adding expert experiences to the experience buffer. An efficient approximate method is developed to identify a teacher policy that generates expert experiences. Numerical studies about a spare part inventory system in the wind energy industry show that the proposed EM-VDTD3 outperforms benchmark methods. [ABSTRACT FROM AUTHOR]

This technical note presents results of a series of monotonic and cyclic DSS laboratory tests performed on five intact marine clays offshore China. The laboratory program aimed to determine the cyclic shear strength and soil deformation properties for offshore foundation design. Various cyclic contour diagrams are provided, including cyclic shear strength and average and cyclic shear strains for different number of cycles. Results of the five clays are discussed and compared with an existing database on static and cyclic strengths of clays. In general, the test data fits well with the database and OCR plays an important role in the cyclic behaviour of the marine clays. The provided cyclic strength parameters for the tested clays can be used as references for similar clays offshore. The purpose of this study is to provide a realistic reference for research and practice offshore China where very few cyclic test results are available for offshore wind energy industry. [ABSTRACT FROM AUTHOR]

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In order to sustain the overall competitiveness of the wind power industry, unrelenting focus is required on working toward the advancement of enabling technologies and research studies that are associated with wind farm systems. First, wind farm technologies that include various turbine generator systems coupled with different power transmission configurations have enormous impact in determining the quality of wind power production. In addition, modern wind farms are expected to implement robust power control algorithms to meet more advanced requirements of electricity generation. Accordingly, this study explores the statuses of wind energy harvesting technologies and wind farm control strategies by discussing their recent and future impact on transforming the wind power industry. Doubly fed induction generator (DFIG)-based wind energy harvesting technology is well-matured and has exhibited an excellent track-record in past and recent experiences, but its capability of being further scalable for large-scale power production is limited as it is largely incompatible with high-voltage power transmission networks. On the other hand, permanent magnet synchronous generator (PMSG)-based technology is making significant advancements to attain the maximum possible efficiency level in greatly facilitating larger scale power generation, although the construction of bulky and costly power transmission systems is required. In this regard, future technological advances in the wind farm industry are expected to reasonably optimize the design and cost of high-voltage power transmission systems. Similarly, an increasing number of research studies are introducing a number of power optimization-based control models to create an ideal integration of the aforementioned wind farm technologies so as to ultimately enhance the reliability of electricity production by maintaining the systems' safety. Yet, additional work is still expected to be undertaken in the future for a more extended evaluation of the performances of many different control models under a similar environment. [ABSTRACT FROM AUTHOR]