Authors: Marcello Catania Giulia Pomaranzi Paolo Schito Alberto Zasso
The aerodynamic behaviour of buildings equipped with porous outer envelopes is governed by the interaction between millimetre-scale geometric features and building-scale flow structures. Explicitly resolving these scales in numerical simulations is computationally prohibitive, making homogenised porous-medium formulations a practical alternative. Among them, the Darcy–Forchheimer (D–F) model is widely adopted; however, the reliability of building-scale predictions critically depends on how its resistance coefficients are identified and validated. This study proposes and assesses a consistent procedure for the determination and application of D–F coefficients for porous screens used in double-skin façade systems. Porous elements are first characterised at the element scale through an analytical derivation based on aerodynamic force coefficients, from fully resolved CFD simulations of representative periodic modules. The resulting D–F coefficients are cross-compared and validated against available wind tunnel data at local Reynolds numbers ReH>3000. Secondly, the calibrated homogenised model is applied to a building-scale double-skin façade configuration. The porous layer is represented as a finite-thickness porous region governed by the identified D–F parameters and analysed through unsteady Reynolds-averaged Navier–Stokes simulations. The model’s capability to reproduce global aerodynamic loads, local pressure distributions, and wake characteristics is evaluated against experimental data. The results demonstrate that a properly calibrated D–F formulation provides an accurate and computationally efficient representation of porous façade systems, bridging element-scale characterisation and structural-scale aerodynamic performance.
]]>Authors: Rohith Giridhar Ray Taghavi Saeed Farokhi
Wind is a significant contributor to global energy requirement, with technological advancements in this industry enabling its rapid growth over the last few decades. The rise in demand for clean energy provides the driving factor to make wind more efficient and widespread. One such solution involves mitigating the aerodynamic noise of wind turbine rotors to harness untapped energy and improve turbine efficiency. Quieter wind turbines gain community acceptance, promoting their widespread application. This article explores passive compliant coatings applied to a flat plate under fully turbulent conditions through Computational Fluid Dynamics (CFD) and wind tunnel testing. It extends prior flat plate investigations by evaluating the noise mitigation potential of passive compliant coatings in the context of wind turbine trailing edge (TE) noise. Two coatings with distinct material properties were investigated through Computational Aeroacoustics Analysis (CAA) and Fluid–Structure Interaction (FSI). While coating-1 (Dow Corning Silastic S-2) increased the overall sound pressure level (OASPL) by 2.89 dB, coating-2 (Dow Corning Sylgard 184) reduced TE noise by 2–4 dB/Hz between 600 and 1575 Hz and lowered the OASPL by 1.85 dB. Within the two configurations investigated, the differences in noise mitigation characteristics may be attributed to variations in coating stiffness and geometric compliance. Based on these simulations, wind tunnel tests were conducted to record noise measurements using coating-2 which revealed a 3.23 dB OASPL reduction, suggesting its suitability for wind turbine noise mitigation applications.
]]>Authors: Arif Ali Rind Muhammad Ramzan Luhur Abdul Latif Manganhar Sher Muhammad Ghoto Sajjad Bhangwar
This study focuses on the aerodynamic performance optimization of the SG6043 airfoil for application in small horizontal axis wind turbines (HAWTs) operating under low-Reynolds-number conditions. Recognizing the critical role of lift-to-drag ratio (Cl/Cd) in maximizing turbine power output, the research investigates the performance of SG6043 through design modifications and computational analysis. Initially, the baseline airfoil’s aerodynamic characteristics were verified using simulation tools like QBlade v0.96.3 software, confirming its previously reported performance. Subsequently, the airfoil was systematically modified by varying key parameters including thickness-to-camber ratio and angle of attack (AOA), operating at different Reynolds numbers. Among the modified versions, SG6043M5-7, SG6043M5-8, and SG6043M5-9 showed significant aerodynamic performance improvement, with SG6042M5-9 achieving the highest Cl/Cd ratio of 193.44 at Re = 6 × 105 and AOA = 3.5°. The results demonstrated that a reduced thickness (5%) combined with moderate to high camber (7–9%) enhances the aerodynamic performance.
]]>Authors: Asaad Hanoon Ziaul Huque Raghava Rao Kommalapati Mst Sumaiya Akter Snigdha Khadiza Akter Keya Kenneth Oluwatobi Fadamiro
As the population increases, the demand for power continues to rise. As fossil fuel resources reduce, wind energy emerges as a sustainable alternative and helps address adverse effects of global warming and environmental pollution caused by fossil fuels. Thus, this study focuses on increasing the efficiency of wind turbines by improving their energy conversion. In this study, the NREL Phase VI wind turbine blade was modified by adding a Gurney flap at trailing edge along the entire span. Computational fluid dynamics simulations using ANSYS CFX 19.2 were performed on the modified blades to evaluate their aerodynamic performance. Three different flap lengths were investigated with six wind speeds varying from 5 m/s to 20 m/s. The results obtained were compared with those from NREL Phase VI original shape and a blade equipped with a winglet. Computational domain was divided into a rotating cylindrical region and a stationary rectangular part. The aerodynamic parameters calculated include torque, thrust, and normal and tangential forces coefficients. At low velocities, the addition of a Gurney flap had an insignificant impact on torque and thrust, whereas at medium to high wind speeds, significant increases were observed on torque, indicating more power production.
]]>Authors: Faisal Mahmuddin Syerly Klara Andi Ardianti Balqis Shintarahayu Zinzaisal Bakri Audrye Kezya Nathania Rampo
In various parts of Indonesia, particularly in coastal areas, wind energy can be used as a source of electricity, using wind turbines, whose energy depends on wind speed. Basically, the number of blades in a wind turbine affects the overall turbine performance. This research analyzes the influence of the blade number on the performance of a small-scale horizontal-axis wind turbine using experimental measurements and Computational Fluid Dynamics (CFD) simulations. The CFD simulations were conducted using ANSYS 2022 R2 software on a small-scale horizontal-axis wind turbine with variations in the number of blades, specifically three, four, and five blades, conducted at various wind speeds. It should be noted that due to the setup limitation in the experiment, only the RPM of the three-bladed turbine was measured. Other variables such as torque and power were derived from CFD simulations. The results of this research indicate that an increase in the number of turbine blades tends to result in higher power output, where the highest output obtained was 46.25 Watts. Furthermore, as the number of turbine blades increases, the turbine efficiency also tends to increase, but as wind speed increases, the efficiency decreases. This is demonstrated by the research results, where a wind turbine with five blades achieved the highest efficiency at a speed of 3 m/s, at 38.00%, while at a speed of 6 m/s, the efficiency was 34.80%. Overall, through experiments and cross-validation of CFD and QBlade version 0.963.1, the present study could confirm the significant effect of the number of blades on the power produced by a small-scale horizontal-axis wind turbine under low-speed conditions.
]]>Authors: Heather Norton Lindsay Miller Marianne Rodgers
As wind farms in North America near the end of their design life, different end-of-life options need to be considered. Common options include decommissioning, lifetime extension, and repowering. In this research, a methodology to support early-stage repowering decisions is presented. Performance decline and repowering forecasts are obtained by combining analysis of past performance data and preliminary site plans for new turbines with turbine performance models from windPRO software. Financial metrics are computed using a simple techno-economic model with parameters informed by historical financial records. Repowering decisions are often sensitive to assumptions on key parameters, such as capital cost of repowering, which are poorly defined at the beginning of the process and subject to change quickly. This makes it difficult to provide guidance that will remain relevant as more information is obtained during future project planning stages. In this work, constrained optimization methods are used to identify sets of the key inputs that lie on the break-even point at which repowering is more profitable than continuing operation. Using this approach, which is novel in this context, the client gains an intuition for the ‘envelope’ within which the recommended guidance still holds. This decision-making process is applied to a case study using performance data and cost ranges from a real, anonymous wind farm.
]]>Authors: Citlali Villalobos-García Luis Francisco Pérez-Moreno Iván Fermín Arjona-Catzim Enrique Rico-García
Wind design aims to ensure the stability, safety, and durability of a structure exposed to wind forces. This comparative study using Computational Fluid Dynamics (CFD) was conducted to evaluate the effects of surrounding structures in wind building design. Two scenarios were analyzed: the first, in which the building was exposed to an open field, and the second, in which the building was surrounded by other buildings of equal or lower height. A CFD model, previously calibrated with experimental data, was used to simulate wind behavior. The results obtained showed significant differences between the two scenarios, confirming that nearby structures have a considerable impact on the distribution of wind pressures on the building. Therefore, the importance of considering surrounding buildings is highlighted. CFD could be a useful complementary tool for obtaining pressure coefficients and for detailed analyses of wind behavior, which could improve the design and safety of buildings under wind loads.
]]>Authors: Firas A. Hadi Rawnak A. Abdulwahab Khattab Al-Khafaji
The research creates classification maps of wind turbine operational speeds based on the wind regimes of four governorates in central and southern Iraq: Wasit, Diwaniyah, Maysan, and Dhiqar. High-resolution wind data from GEOSUN resource maps, together with statistical analysis of the Weibull distribution, are used to derive site-specific shape and scale parameters, which are then utilized to calculate the ideal cut-in, rated, and cut-out wind speeds for each location. A turbine performance index integrates capacity factor and normalized power output to determine the turbine speed combination that optimizes energy production for the local wind distribution. The resultant maps exhibit distinct geographical gradients: in all four governorates, cut-in, rated, and cut-out speeds consistently escalate towards the eastern regions of the research area, therefore broadening the range of technologically suitable turbines. Quantitatively, Wasit demonstrates the highest rated wind speeds, ranging from approximately 11.1 to 14.9 m per second, and cut-out speeds from about 20.5 to 27.6 m per second, indicating superior wind resource quality relative to other governorates. In contrast, Diwaniyah is suitable for lower-speed turbines, with minimum rated speeds between 8.9 and 9.5 m per second and minimum cut-out speeds around 16.6 to 17.6 m per second. Analysis of wind direction indicates that around fifty percent of the wind power potential originates from the northwest sector, suggesting that turbines should be aligned toward the northwest to optimize yearly energy acquisition. The maps serve as an effective decision support instrument that connects quantitative wind resource assessment to turbine operational specifications, facilitating expedited preliminary turbine selection, enhanced energy efficiency, and diminished dependence on traditional fossil fuel power plants in areas experiencing persistent electricity deficits.
]]>Authors: Yujiao Liu Zixin Yang Yang Zhao Daocheng Zhou
Accurate wind field simulation in forest areas is crucial for wind energy development but remains challenging for traditional WRF models due to complex terrain and vegetation heterogeneity. This study proposes a multi-source optimization framework integrating seasonal PBL scheme selection, localized leaf area index (LAI) adjustment, and 3DVAR data assimilation to improve WRF performance in forested terrain. The framework was validated using observations at 20 m, 50 m, and 100 m heights in Maoershan forest area. Results show that: (1) PBL schemes exhibit significant seasonal dependence—YSU performs best in spring (unstable conditions), while MYJ shows slight advantages near the surface in winter (stable conditions). (2) Localized LAI correction reduces near-surface wind speed bias by 35% and improves wind direction accuracy by 28%, with stronger effects in summer. (3) 3DVAR assimilation further enhances accuracy, achieving correlation coefficients of 0.869 for wind speed and 0.813 for wind direction, with greater improvements in summer and near the surface. (4) Winter wind power density at 100 m reaches 475 W/m2, 38% higher than summer, indicating stable exploitable resources. The proposed framework provides a replicable methodology for wind field simulation in forest regions worldwide.
]]>Authors: Bernhard Rösch Konstantin Zacharias Luca Fabian Schlaug Daniel Westerfeld Stefan Geißelsöder Alexander Buchele
Accurate wind flow prediction is essential for various applications, including the placement of wind turbines and a multitude of environmental assessments. Traditionally this can be achieved by using time-consuming computational fluid dynamics (CFD) simulations on reanalysis data. This study explores the performance of an autoencoder (AE) and a variational autoencoder (VAE) in approximating downscaled wind speed and direction using real-world reanalysis data and reference geo- and vegetation data. The AE model was trained for 2000 epochs and demonstrates the ability to replicate wind patterns with a mean absolute error (MAE) of approximately −0.9. However, the AE model exhibited a consistent underestimation of wind speeds and a directional shift of approximately 10 degrees compared to CFD reference simulations. The VAE model produced visually improved results, capturing complex wind flow structures more accurately than the AE model. It mainly achieves better local accuracy and a reduced variance of the results. The overall result suggests that while autoencoders can approximate wind flow patterns, challenges remain in capturing the full variability of wind speeds and directions with sufficient precision. The study highlights the importance of balancing reconstruction accuracy and latent space regularization in VAE models. Future work should focus on optimizing model architecture and training strategies to enhance accuracy, prediction reliability and generalizability across diverse wind conditions and various locations.
]]>Authors: Karl Gebrael Glib Ivanov Leon van Jaarsveldt
Floating offshore wind holds immense promise for nations with deep coastal waters and robust wind resources. Taiwan, with 90% of its territorial waters deeper than 50 m and consistently strong wind speeds, is well-positioned to lead in this domain. However, recent project withdrawals by major developers have raised concerns over the sector’s viability. This paper investigates the stagnation of Taiwan’s floating wind industry by comparing its development framework with that of France, now a global frontrunner in floating offshore wind. Through a mixed-method approach combining literature review, techno-economic benchmarking, and thematic analysis of interviews with industry leaders, the research identifies key barriers in Taiwan, including insufficient port infrastructure, unclear regulatory frameworks, fragmented supply chains, and a lack of financial incentives. Drawing on lessons from France’s structured tendering system and phased industrial strategy, the paper outlines actionable recommendations for revitalizing Taiwan’s floating wind sector. These include policy reforms, supply chain enhancements, and demonstration-scale deployments. The findings aim to inform both policymakers and industry stakeholders in shaping a more viable future for floating offshore wind in Taiwan.
]]>Authors: Welcome Khulekani Ntuli Musasa Kabeya
The integration of renewable energy sources (RESs) into modern power systems has introduced significant challenges in maintaining system stability and reliability. Among these challenges, load frequency control (LFC) has become a vital area of research. The variable nature of RESs, such as wind and solar, along with their intermittent availability, necessitates advanced management systems for effective frequency regulation. LFC plays a crucial role in ensuring the stability and performance of electrical power systems by managing frequency through the balance of supply and demand, accounting for variations in load, generation, and other disturbances within the system. In traditional power systems, LFC is achieved through a combination of primary, secondary, and tertiary control mechanisms. However, the advent of smart grids has considerably complicated and enhanced the potential for LFC. In these smart grids, which leverage digital communication, sensors, and automation technologies, LFC becomes more intricate and adaptable. These systems not only utilize traditional centralized control but also incorporate RESs, decentralized resources, energy storage solutions, and real-time data to improve frequency management. This research methodically evaluates current LFC techniques using a hierarchical control and technology-focused framework, classifying approaches as conventional, intelligent, and hybrid control schemes within centralized and decentralized system architectures. An evaluative analysis reveals that while intelligent and hybrid control strategies markedly enhance dynamic frequency response and robustness with substantial renewable energy source (RES) integration, persistent challenges remain regarding controller coordination, scalability, computational requirements, and real-time execution. The analysis highlights adaptive hybrid intelligent control schemes, namely those that combine data-driven learning with physical system models, as the most promising avenue for future research, particularly in low-inertia and highly dispersed smart grid scenarios.
]]>Authors: Svetlana Orlova Nikita Dmitrijevs Marija Mironova Edmunds Kamolins Vitalijs Komasilovs
Forests play a vital role in influencing wind flow by modifying turbulence intensity and vertical wind shear. Because wind turbines are susceptible to these conditions, accurately characterising wind flow in forested environments is vital to ensuring structural reliability and realistic energy-yield assessments. In Latvia, where approximately 51.3% of the territory is covered by forests; the likelihood of wind turbine deployment in such areas is considerable. However, wind behaviour within and above forests is complex and strongly influenced by canopy effects, which in turn affect wake dynamics, structural fatigue, and power production. Advancing research in this field is therefore crucial for improving the accuracy of wind resource assessment and supporting evidence-based engineering solutions that enable the sustainable development of wind energy. Wind conditions were evaluated using NORA3 reanalysis data. Wake effects were simulated with the Jensen wake model to estimate annual energy production (AEP), which then informed levelised cost of energy (LCOE) calculations at various hub heights. The results indicate clear seasonal variability and show that increasing hub height leads to higher AEP and lower LCOE, owing to higher wind speeds and reduced turbulence. For forest heights of 0–25 m, the AEP loss increases from 7.8% (hub height = 199 m) to 22.9% (hub height = 114 m). Higher hub heights are also less sensitive to canopy-induced variability, reducing the impact of forest-related turbulence on energy production.
]]>Authors: Paula Rose de Araújo Santos Louise Pereira da Silva Susane Eterna Leite Medeiros Raphael Abrahão
Considering the growing potential of artificial intelligence (AI), its application has become increasingly relevant in climate-related studies and energy assessments. In this study, the Random Forest algorithm was applied to impute missing values in time series of air temperature, wind speed, atmospheric pressure, and wind direction. The performance of the data imputation was evaluated using RMSE, MSE, and MAE metrics, as well as the Kolmogorov–Smirnov (KS) test, which supported the selection of the most appropriate exogenous variable. Subsequently, short-term wind speed forecasting was performed using the SARIMAX model, and monthly energy generation was estimated for the V80/2000, SWT-2.3-101, and S95/2100 wind turbine models. The proposed methodology was applied to data from 50 conventional meteorological stations of the National Institute of Meteorology (INMET) located in Northeast Brazil. The results indicate that the gap-filling procedure was effective, particularly for wind speed and mean air temperature. Moreover, the SARIMAX model demonstrated good forecasting performance at most of the analyzed stations. Overall, the findings suggest that the majority of the locations analyzed present favorable conditions for wind-based electricity generation.
]]>Authors: Gaoxue Cheng Wei Ma Yalong Lan Hongrui Ping Shijin Ma Fulong Wei Zhenbo Gao Guanlin Lu Lidong Zhang
Considering the global shift towards clean energy, advancing wind power generation technology is crucial. In complex terrain, turbines face significant challenges, such as increased fatigue loads from turbulent airflow, which reduce efficiency and structural integrity. Yaw optimization has emerged as a key solution to enhance performance in these environments. By dynamically adjusting the nacelle orientation, it improves wind capture, mitigates load fluctuations, and alleviates stress on turbine components. This not only boosts energy output but also extends equipment lifespan and reduces operational costs, supporting the economic feasibility of wind projects in complex terrain. This paper reviews current research and development trends in yaw optimization for wind farms in such settings, focusing on adaptive control strategies and the balance between load management and power efficiency. It examines the impact of different yaw optimization approaches on both individual turbines and overall wind farm performance. In conclusion, tailored yaw optimization strategies are proposed to maximize wind resource utilization in complex terrain, providing a reference for more resilient and efficient wind energy systems.
]]>Authors: Eiji Sakai Atsushi Hashimoto Kazuki Nanko Toshihiko Takahashi Hiroyuki Nishida Hidetoshi Tamura Yasuo Hattori Yoshikazu Kitano
Leading-edge erosion of wind turbine blades caused by repeated raindrop impingement can significantly reduce power output and increase maintenance costs. This study develops a rain erosion atlas for Japan over 11 years from 2006 to 2016 based on the CRIEPI-RCM-Era2 dataset. The NREL 5 MW, DTU 10 MW, and IEA 15 MW wind turbines were employed to evaluate the incubation time (erosion onset time) of commercial polyurethane-based coating at the blade tip. Erosion progression was simulated using an empirical damage model that relates raindrop impingement and impact velocity to the incubation time. The rain erosion atlas reveals a clear correlation between wind turbine size and erosion risk: the NREL 5MW turbine shows an incubation time of 3–12 years, the DTU 10MW turbine 1–4 years, and the IEA 15MW turbine 0.5–2 years. Shorter incubation times are observed on the Pacific Ocean side, where annual precipitation is higher than on the Sea of Japan side. Additionally, the influence of coating degradation due to ultraviolet radiation was assessed using solar radiation data, revealing a further reduction in incubation time on the Pacific Ocean side. Finally, the potential of erosion-safe mode operation was examined, demonstrating its effectiveness in alleviating erosion progression.
]]>Authors: Igor Esau Pravin Punde Yngve Birkelund
Wind energy has the potential to become an important source of energy for remote Arctic regions. However, there are risks associated with the exposure of coastal wind parks to extremely strong winds caused by storms and polar lows. Extreme winds can either enhance or reduce wind energy production. The outcomes largely depend on the coastal landscape surrounding the wind park. To address these questions, we conducted a series of simulations using the Weather Research and Forecasting (WRF) model. This study focuses on one of the strongest wind events along the western Norwegian coast—the landfall of the storm “Ylva” (24–27 November 2017). The study employs terrain-resolving downscaling by zooming in on the area of the Kvitfjell–Raudfjell wind park, Norway. The terrain-resolving WRF simulations reveal stronger winds at turbine hub height (80 m to 100 m above the ground level) in the coastal area. However, it was previously overlooked that the landfall of an Atlantic storm, which approaches this area from the southwest, brings the strongest winds from southeast directions, i.e., from the land. This creates geographically extensive and vertically deep wind-sheltered areas along the coast. Wind speeds at hub height in these sheltered areas are reduced, while they remain extreme over wind-channeling sea fjords. The novelty and applied value of this study is that it reveals an overlooked opportunity for optimal wind park siting. The coastal wind parks can take advantage of both sustained westerly winds during normal weather conditions and wind sheltering during extreme storm conditions. We found that the Kvitfjell–Raudfjell location is nearly optimal with respect to the extreme winds of “Ylva.”
]]>Authors: Muhammad Rashid Abdur Raheem Rabia Shakoor Muhammad I. Masud Zeeshan Ahmad Arfeen Touqeer Ahmed Jumani
An optimal topographical arrangement of wind turbines (WTs) is essential for increasing the total power production of a wind farm (WF). This work introduces PSO-GA, a newly formulated algorithm based on the hybrid of Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) method, to provide the best possible and reliable WF layout (WFL) for enhanced output power. Because GA improves on PSO-found solutions while PSO investigates several regions; therefore, hybrid PSO-GA can effectively handle issues involving multiple local optima. In the first phase of the framework, PSO improves the original variables; in the second phase, the variables are changed for improved fitness. The goal function takes into account both the power production of the WF and the cost per power while analyzing the wake loss using the Jenson wake model. To evaluate the robustness of this strategy, three case studies are analyzed. The algorithm identifies the best possible position of turbines and strictly complies with industry-standard separation distances to prevent extreme wake interference. This comparative study on the past layout improvement process models demonstrates that the proposed hybrid algorithm enhanced performance with a significant power improvement of 0.03–0.04% and a 24–27.3% reduction in wake loss. The above findings indicate that the proposed PSO-GA can be better than the other innovative methods, especially in the aspects of quality and consistency of the solution.
]]>Authors: Dimitra Triantafyllidou Dimitra G. Vagiona
The purpose of this study is to determine the optimal location for siting an onshore wind farm on the island of Skyros, thereby maximizing performance and minimizing the project’s environmental impacts. Seven evaluation criteria are defined across various sectors, including environmental and economic sectors, and six criteria weighting methods are applied in combination with four multicriteria decision-making (MCDM) ranking methods for suitable areas, resulting in twenty-four ranking models. The alternatives considered in the analysis were defined through the application of constraints imposed by the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD RES), complemented by exclusion criteria documented in the international literature, as well as a minimum area requirement ensuring the feasibility of installing at least four wind turbines within the study area. The correlations between their results are then assessed using the Spearman coefficient. Geographic information systems (GISs) are utilized as a mapping tool. Through the application of the methodology, it emerges that area A9, located in the central to northern part of Skyros, is consistently assessed as the most suitable site for the installation of a wind farm based on nine models combining criteria weighting and MCDM methods, which should be prioritized as an option for early-stage wind farm siting planning. The results demonstrate an absolute correlation among the subjective weighting methods, whereas the objective methods do not appear to be significantly correlated with each other or with the subjective methods. The ranking methods with the highest correlation are PROMETHEE II and ELECTRE III, while those with the lowest are TOPSIS and VIKOR. Additionally, the hierarchy shows consistency across results using weights from AHP, BWM, ROC, and SIMOS. After applying multiple methods to investigate correlations and mitigate their disadvantages, it is concluded that when experts in the field are involved, it is preferable to incorporate subjective multicriteria analysis methods into decision-making problems. Finally, it is recommended to use more than one MCDM method in order to reach sound decisions.
]]>Authors: María Florencia Luna Rafael Beltrán Oliva Jacobo Omar Salvador
Southern Patagonia in Argentina possesses a world-class wind resource; however, its remote location challenges long-term monitoring. This study presents the first long-term Doppler LiDAR-based wind characterization in the region, analyzing six months of high-resolution data at a 100 m hub height. Power for the LiDAR is provided by a hybrid system combining photovoltaic (PV) and grid sources, with remote monitoring. The results reveal two distinct seasonal regimes identified through a multi-model statistical framework (Weibull, Lognormal, and non-parametric Kernel Density Estimation: a high-energy summer with concentrated westerly flows and pronounced diurnal cycles (Weibull scale parameter A ≈ 11.9 m/s), and a more stable autumn with a broad wind direction spectrum (shape parameter k ≈ 2.86). Energy output, simulated using Windographer v5.3.12 (Academic License) for a Vestas V117-3.3 MW turbine, shows close alignment (~15% difference) with the operational Bicentenario I & II wind farm (Jaramillo, AR), validating the site’s wind energy potential. This study confirms the viability of utility-scale wind power generation in Southern Patagonia and establishes Doppler LiDAR as a reliable tool for high-resolution wind resource assessment in remote, high-wind environments.
]]>Authors: Giusep Baca Gabriel Santos Leandro Salviano
The depletion of fossil fuel resources and the growing need for sustainable energy solutions have increased interest in vertical axis wind turbines (VAWTs), which offer advantages in urban and variable-wind environments but often exhibit limited performance at low tip speed ratios (TSRs). This study optimizes VAWT aerodynamic behavior across a wide TSR range by varying three geometric parameters: maximum thickness position (a/b), relative thickness (m), and pitch angle (β). A two-dimensional computational fluid dynamics (CFD) framework, combined with the Metamodel of Optimal Prognosis (MOP), was used to build surrogate models, perform sensitivity analyses, and identify optimal profiles through gradient-based optimization of the integrated Cp–λ curve. The Joukowsky transformation was employed for efficient geometric parameterization while maintaining aerodynamic adaptability. The optimized airfoils consistently outperformed the baseline NACA 0021, yielding up to a 14.4% improvement at λ=2.64 and an average increase of 10.7% across all evaluated TSRs. Flow-field analysis confirmed reduced separation, smoother pressure gradients, and enhanced torque generation. Overall, the proposed methodology provides a robust and computationally efficient framework for multi-TSR optimization, integrating Joukowsky-based parameterization with surrogate modeling to improve VAWT performance under diverse operating conditions.
]]>Authors: Ahmed Badawi Wasel Ghanem Nasser Ismail Alhareth Zyoud I. M. Elzein Ashraf Al-Rimawi
This research presents a detailed assessment of the wind power potential in six Palestinian cities—Bethlehem, Jericho, Jenin, Nablus, Ramallah, and Tulkarm—utilizing daily wind speed data from the years 2015 to 2021. The primary goal of this study is to formulate a robust, data-driven framework for the strategic placement of turbines and the economical production of energy in areas with limited wind resources. A critical aspect of this research is the application of nine numerical methods, including the Maximum Likelihood Method (MLM) and the Energy Pattern Factor Method (EPF), to analyze the wind data. These methods were employed to estimate the shape and scale parameters of the Probability Distribution Function (PDF) that represents the Weibull distribution for various shape factor values. The accuracy of the numerical methods was validated through five statistical tools, including the Root Mean Square Error (RMSE) and Chi-square tests (X2). The Weibull parameters obtained from the numerical techniques indicated shape factors ranging from 1.27 to 1.96 and scale factors between 1.16 and 3.21 m/s. The energy output was calculated based on the swept area of the wind turbine, following Betz’s limit. The estimated annual energy production per square meter in the six cities is as follows: Ramallah—123 kWh/m2, Bethlehem—24.42 kWh/m2, Jenin—31.12 kWh/m2, Nablus—22 kWh/m2, Tulkarm—15.5 kWh/m2, and Jericho—10.36 kWh/m2. A 5 kW small-scale wind turbine was utilized to evaluate the technical feasibility, sustainability, and economic viability of small-scale wind energy applications. The anticipated energy output from the proposed wind turbine is 2054 kWh, with an estimated payback period of approximately 11.6 years.
]]>Authors: F. Díaz-Canul J. O. Aguilar N. Rosado-Hau E. Simá O. A. Jaramillo
The parametric design of a low-power (<1 kW) H-type vertical-axis wind turbine tailored to the wind conditions of the Yucatán Peninsula is presented. Nine airfoils were evaluated using the Double Multiple Streamtube method and Qblade Lifting-Line Theory numerical simulations, considering variations in solidity (σ = 0.20–0.30), aspect ratio (Ar = H/R = 2.6–3.0), number of blades (2–5), and a swept-area constraint of 4 m2. The parametric study shows that fewer blades increase Cp, although a three-blade rotor improves start-up torque, vibration mitigation, and load smoothing. The recommended configuration—three blades, Ar = 2.6, σ = 0.30 and S1046 (or NACA 0018) operated near λ ≈ 3.75—balances efficiency and start-up performance. For the representative mean wind velocity of 5 m/s, typical of the Yucatán Peninsula, the VAWT achieves a maximum output of 136 W at 220 rpm. Under higher-wind conditions observed in specific sites within the region, the predicted maximum output increases to 932 W at 380 rpm.
]]>Authors: Huzaifah Zahid Muhammad Rashad Naveed Ashraf
Voltage instability and power quality degradation represent critical barriers to the reliable operation of modern wind farm-based microgrids. As the share of distributed wind generation continues to grow, fluctuating wind speeds and variable reactive power demands increasingly challenge grid stability. This study proposes an adaptive decentralized framework integrating a Dynamic Distribution Static Compensator (DSTATCOM) with an Artificial Neuro-Fuzzy Inference System (ANFIS)-based control strategy to enhance dynamic voltage and frequency stability in wind farm microgrids. Unlike conventional centralized STATCOM configurations, the proposed system employs parallel wind turbine modules that can be selectively switched based on voltage feedback to maintain optimal grid conditions. Each turbine is connected to a capacitive circuit for real-time voltage monitoring, while the ANFIS controller adaptively adjusts compensation signals to ensure minimal voltage deviation and reduced harmonic distortion. The framework was modeled and validated in the MATLAB/Simulink R2023a environment using the Simscape Power Systems toolbox. Simulation results demonstrated superior transient response, voltage recovery, and power factor correction compared with traditional PI and fuzzy-based controllers, achieving a total harmonic distortion below 2.5% and settling times under 0.5 s. The findings confirm that the proposed decentralized DSTATCOM–ANFIS approach provides an effective, scalable, and cost-efficient solution for maintaining dynamic stability and high power quality in wind farm based microgrids.
]]>Authors: Hudhaifa Hamzah Ali Alkhabbaz Aisha Koprulu Laith M. Jasim Ibrahim K. Alzubaidi Abdulelah Hameed Yaseen Ho-Seong Yang Young-Ho Lee
The growing demand for renewable energy has amplified the need for efficient and reliable wind turbine technologies, where understanding aerodynamic performance and aeroelastic behavior plays a critical role. In this study, a high-fidelity computational fluid dynamics (CFD) model was developed to analyze the aerodynamic loads and structural responses of a 2 kW horizontal-axis wind turbine, while an artificial neural network (ANN) was trained using CFD-generated data to predict power output and aeroelastic characteristics. The work combines ANN predictions and CFD simulations to determine the feasibility of machine learning as a surrogate model, which is much less expensive in terms of computational costs and time, with no negative effects on the accuracy. Findings indicate ANN predictions are closely comparable to CFD results with under 5–7% deviation at optimal blade pitch angles, which was shown to be very reliable in capturing nonlinear aerodynamic trends at different wind speeds and blade pitch angles. In addition, the obtained result emphasizes the example of the trade-off between aerodynamic efficiency and structural safety, where the largest power coefficient (0.42) was achieved at 0° pitch and the tip deflections were reduced by almost 60% as the pitch was raised to 5°. Such results substantiate the usefulness of ANN-based methods in the rapid aerodynamic and aeroelastic simulation of wind turbines and provide a prospective direction for effectively designed wind power generation and optimization.
]]>Authors: Jay Prakash Goit
The current study investigates the effect of terrain features on wind resources in a region with extremely diverse terrain. To that end, a case study of Nepal based on annual wind data collected from 10 different sites is performed. The evaluation of mean wind speeds using Weibull probability density functions (PDFs) shows that complex-terrain sites exhibit greater variability in 10-min average wind speeds relative to the annual average wind speeds. This pattern is also evident in comparisons of short- and long-term average wind speeds. At the complex-terrain sites, the wind speeds exhibited strong short-term variations, suggesting that local terrain effects dominate over seasonal wind variation. Terrain complexity also strongly affected turbulence. The flat-terrain sites showed turbulence intensities below the lowest IEC category turbulence profile, while the complex-terrain sites exceeded the highest IEC profile. This indicates that the IEC standard may require modification based on site complexity parameters, such as the standard deviation of elevation fluctuations. The power law exponent (α), used to extrapolate wind speeds to higher elevations, deviated notably from the typical 1/7 value, even in flat terrain. Finally, a power potential analysis indicated that three sites with higher mean wind speeds achieved higher capacity factors.
]]>Authors: Areeg Ebrahiem Elngar Asmaa Sobhy Sabik Ahmed Hassan Adel Adel S. Nada
Wind energy has become a cornerstone of sustainable electricity generation, yet the reliable integration of wind energy conversion systems (WECSs) into modern grids remains challenged by dynamic variations in wind speed and stringent fault ride-through (FRT) requirements. Among the available technologies, the Doubly Fed Induction Generator (DFIG) and the Permanent Magnet Synchronous Generator (PMSG) dominate commercial applications; however, a comprehensive comparative assessment under diverse grid and fault scenarios is still limited. This study addresses this gap by systematically evaluating the performance of DFIG- and PMSG-based WECSs across three operating stages: (i) normal operation at constant speed, (ii) variable wind speed operation, and (iii) grid fault conditions including single-line-to-ground, line-to-line, and three-phase faults. To enhance fault resilience, a DC-link Braking Chopper is integrated into both systems, ensuring a fair evaluation of transient stability and compliance with low-voltage ride-through (LVRT) requirements. The analysis, performed using MATLAB/Simulink, focuses on active and reactive power, rotor speed, pitch angle, and DC-link voltage dynamics. The results reveal that PMSG exhibits smoother transient responses and lower overshoot compared to DFIG. Under fault conditions, the DC-link Braking Chopper effectively suppresses voltage spikes in both systems, with DFIG achieving faster reactive power recovery in line with grid code requirements, while PMSG ensures more stable rotor dynamics with lower oscillations. The findings highlight the complementary strengths of both technologies and provide useful insights for selecting appropriate WECS configurations to improve grid integration and fault ride-through capability.
]]>Authors: Mehroz Fatima Wasiq Ullah Faisal Khan U. B. Akuru
The scaling effect of machines from kW to MW greatly affects electromagnetic performance and needs to be investigated for different machines. Therefore, this paper presents a comprehensive comparative study on the intriguing electromagnetic performance of contra-rotating permanent-magnet vernier machines and dual-port, wound-field-excited, flux-switching machines at the MW power level for contra-rotating wind turbine applications. The analysis evaluates both machines across various slot/pole combinations while maintaining constant key design parameters. The electromagnetic performance analysis reveals that the permanent-magnet vernier machine (PMVM) exhibits superior torque and power, with minimal cogging torque compared to the wound-field flux-switching machine (WFFSM). Conversely, the WFFSM outperforms the PMVM in terms of power factor and efficiency. This study provides valuable perspectives on the strengths and weaknesses of each machine, highlighting their potential for contra-rotating turbine and wind power generation. Finally, to justify the findings of the finite element analysis and the proof of concept, an experimental prototype is tested to validate the study.
]]>Authors: Edgar A. Manzano Ruben E. Nogales Alberto Rios
The present study focuses on wind power forecasting (WPF) models based on deep neural networks (DNNs), aiming to evaluate current approaches, identify gaps, and provide insights into their importance for the integration of Renewable Energy Sources (RESs). The systematic review was conducted following the methodology of Kitchenham and Charters, including peer-reviewed articles from 2020 to 2024 that focused on WPF using deep learning (DL) techniques. Searches were conducted in the ACM Digital Library, IEEE Xplore, ScienceDirect, Springer Link, and Wiley Online Library, with the last search updated in April 2024. After the first phase of screening and then filtering using inclusion and exclusion criteria, risk of bias was assessed using a Likert-scale evaluation of methodological quality, validity, and reporting. Data extraction was performed for 120 studies. The synthesis established that the state of the art is dominated by hybrid architectures (e.g., CNN-LSTM) integrated with signal decomposition techniques like VMD and optimization algorithms such as GWO and PSO, demonstrating high predictive accuracy for short-term horizons. Despite these advancements, limitations include the variability in datasets, the heterogeneity of model architectures, and a lack of standardization in performance metrics, which complicate direct comparisons across studies. Overall, WPF models based on DNNs demonstrate substantial promise for renewable energy integration, though future work should prioritize standardization and reproducibility. This review received no external funding and was not prospectively registered.
]]>Authors: Inajara Rutyna
Day-ahead wind power forecasting is often limited to on-site Supervisory Control and Data Acquisition (SCADA) datasets without Numerical Weather Prediction (NWP) information. In this regime, practitioners extend autoregressive windows over many variables, so the input size grows with both features and lags. Many lag–feature pairs are redundant, increasing the training time and overfitting risk. A lightweight, differentiable joint gate over the lag–feature plane trained with a temperature-annealed sigmoid is proposed. Sparsity is induced by capped penalties that (i) bound the total open mass to the top-M features and (ii), within each selected feature, bound the mass to the top-k lags. An additional budget-aware off-state term pushes unused logits negative in proportion to the excess density over the (M×k) budget. A lightweight, per-feature softmax pooling head supplies the forecasting loss during selection. After training, the learned probabilities are converted into compact, non-contiguous lag–feature subsets (top-M features; per-feature top-k lags) and reused by downstream predictors. Tests on the Offshore Renewable Energy (ORE) Catapult Platform for Operational Data (POD) from the Levenmouth Demonstration Turbine (LDT) dataset show that the joint gate reduces the input dimensionality and training time while improving accuracy and stability relative to Pearson’s correlation, mutual information, and cross-correlation function selectors.
]]>Authors: Aly Mousaad Aly Hannah DiLeo
Bridges, as critical transportation infrastructure, are highly vulnerable to aerodynamic forces, particularly vortex-induced vibrations (VIV), which severely compromise their structural integrity and operational safety. These low-frequency, high-amplitude vibrations are a primary challenge to serviceability and fatigue life. Ensuring the resilience of these structures demands advanced understanding and robust mitigation strategies. This paper comprehensively addresses the multifaceted challenges of bridge aerodynamics, presenting an in-depth analysis of contemporary testing methodologies and innovative solutions. We critically examine traditional wind tunnel modeling, elucidating its advantages and inherent limitations, such as scale effects, Reynolds number dependence, and boundary interference, which can lead to inaccurate predictions of aerodynamic forces and vibration amplitudes. This scale discrepancy is critical, as demonstrated by peak pressure coefficients being underestimated by up to 64% in smaller-scale wind tunnel environments compared to high-Reynolds-number open-jet testing. To overcome these challenges, the paper details the efficacy of open-jet testing at facilities like the Windstorm Impact, Science, and Engineering (WISE) Laboratory, demonstrating its superior capability in replicating realistic atmospheric boundary layer flow conditions and enabling larger-scale, high-Reynolds-number testing for more accurate insights into bridge behavior under dynamic wind loads. Furthermore, we explore the design principles and applications of various aerodynamic mitigation devices, including handrails, windshields, guide vanes, and spoilers, which are essential for altering airflow patterns and suppressing vortex-induced vibrations. The paper critically investigates the innovative integration of green energy solutions, specifically solar panels, with bridge structures. This study presents the application of solar panel arrangements to provide both renewable energy production and verifiable aerodynamic mitigation. This strategic incorporation is shown not only to harness renewable energy but also to actively improve aerodynamic performance and mitigate wind-induced vibrations, thereby fostering both bridge safety and sustainable infrastructure development. Unlike previous studies focusing primarily on wind loads on PV arrays, this work demonstrates how the specific geometric integration of solar panels can serve as an active aerodynamic mitigation device for bridge decks. This dual functionality—harnessing renewable energy while simultaneously serving as a passive geometric countermeasure to vortex-induced vibrations—marks a novel advancement over single-purpose mitigation technologies. Through this interdisciplinary approach, the paper seeks to advance bridge engineering towards more resilient, efficient, and environmentally responsible solutions.
]]>Authors: David Cunningham Rubina Ramponi Reamonn MacReamoinn Jennifer Keenahan
In anticipation of the implementation of the Second-Generation Eurocodes, evaluating the suitability of these standards is necessary to ensure the structural safety and sustainable design of Ireland’s future building stock. This paper provides a detailed comparative analysis of the wind loading codes of practice relevant to Ireland: The Irish National Annex to EN1991-1-4 (2005) and the draft version of the Second-Generation Eurocode, EN1991-1-4 (2025). Quantitative evaluation is conducted across a range of building typologies, with calculations performed for various sites and structural geometries. The findings reveal marked differences in wind load predictions between the codes, particularly affecting base shear values and net pressure coefficients. Areas of concern regarding structural design efficiency and safety for future building structures in Ireland are outlined. The significant inconsistencies between provisions within the codes of practice are identified and critically evaluated from both theoretical and practical perspectives, providing insight into the optimal solution for implementation in Irish engineering practice.
]]>Authors: Rossen Iliev
This article presents a methodology for the synthesis of horizontal-axis wind turbines operating on the principle of lift. The profile geometry is synthesized using the Vortex–source distribution method following Glauert’s approach. The blade shape is developed using the Blade Element Momentum Theory. Efficiency is determined with Computational Fluid Dynamics. The methodology uses a multifactor numerical experiment, with the objective function defined as maximizing lift-to-drag ratio of the blade profile. Validation of the obtained power curves is performed with QBlade and XFoil and confirmed experimentally on a laboratory test bench. The proposed methodology demonstrates improved accuracy in predicting the power coefficient and the optimal operation regime of horizontal-axis wind turbines at low Reynolds numbers.
]]>Authors: Karim Farokhnia
Windborne debris generated during tornadoes and hurricanes plays a critical role in building damage. This damage occurs either through direct impact on structural and nonstructural components or indirectly by increasing internal pressure when debris penetrates openings (e.g., windows and doors) or creates new ones. These breaches can significantly raise internal pressure, even at lower wind speeds compared to debris-free conditions. Current provisions in ASCE 7, the nationally adopted standard for wind load calculations in the United States, account for factors such as building geometry, location, and exposure category. However, they do not consider the effects of windborne debris on internal pressure coefficients. This study proposes an enhancement to ASCE 7 by incorporating debris effects through the use of a more conservative enclosure classification. Real-world damage observations from three tornado-impacted residential buildings are presented, followed by a failure mechanism analysis, supporting analytical fragility data, and numerical simulations of debris effects on building damage. The findings suggest that treating buildings as Partially Enclosed under ASCE 7 can more accurately reflect debris-induced internal pressures and improve building resilience under extreme wind events.
]]>Authors: Mohamed Noufel Ajmal Khan Mertol Tüfekci
This study investigates the topology optimisation of a composite wind turbine blade with the objective of improving its structural performance under static and dynamic constraints. Two distinct optimisation strategies—based on static deformation limits and modal frequency enhancement—are employed to achieve mass reduction while maintaining or improving mechanical performance. The optimisation process incorporates modal characterisation of the first ten natural frequencies and a detailed static stress analysis. Results indicate that the optimised designs achieve a notable increase in the fundamental natural frequency of the blade—from 2.32 Hz to 2.99 Hz—and reduce the overall mass by approximately 49%, lowering it from 4.55 × 105 kg to around 2.34 × 105 kg compared to the original configuration. In particular, the optimised geometry offers improved stiffness and a more uniform stress distribution, especially in the flapwise bending and torsional modes. Higher-order torsional frequencies remain well-separated from typical excitation sources, minimising resonance risks. These findings highlight the effectiveness of constraint-driven topology optimisation in enhancing structural performance and reducing material usage in wind turbine blade design.
]]>Authors: Uriel Castilla Batun Mohamed E. Zayed Mohamed Ghazy Shafiqur Rehman
Mexico holds significant potential for wind energy development, owing to its strategic geographic location and extensive coastlines. This review article systematically explores the technical, environmental, and economic aspects of wind energy in five different climatic zones in Mexico, reviewing potential zones for wind energy development, with the focus on the key case studies, ongoing project, and wind power performance metrics. It also critically examines the key challenges and opportunities within Mexico’s wind energy portfolio, with a focus on social, economic, environmental, and regulatory dimensions that influence the sector’s development and long-term sustainability. The results indicate that Oaxaca leads Mexico’s onshore wind potential with a power density of 761 W/m2, followed by strong resources in Tamaulipas and Baja California, where wind speeds exceed 6 m/s. For offshore wind potential, Isthmus of Tehuantepec demonstrates outstanding offshore potential, with wind power densities exceeding 1000 W/m2 and wind speeds above 8 m/s. Major challenges include inconsistent or unclear governmental policies regarding renewable energy incentives, regulatory uncertainties, and social resistance from local communities concerned about environmental impacts and land use. These obstacles underline the need for integrated, transparent policies and inclusive engagement strategies to carry out the full potential of wind energy in Mexico.
]]>Authors: Amineddin Salimi Ayşegül Yurtyapan Mahmoud Ouria Zihni Turkan Nuran K. Pilehvarian
Natural cooling and ventilation have been fundamental principles in vernacular architecture for millennia, shaping sustainable building practices across diverse climatic regions. This paper examines the historical evolution, technological advancements, environmental benefits, and prospects of passive cooling strategies, with a particular focus on wind catchers. Originating in Mesopotamian, Egyptian, Caucasia, and Iranian architectural traditions, these structures have adapted over centuries to maximize air circulation, thermal regulation, and humidity control, ensuring comfortable indoor environments without reliance on mechanical ventilation. This study analyzes traditional wind catcher designs, highlighting their geometric configurations, airflow optimization, and integration with architectural elements such as courtyards and solar chimneys. Through a comparative assessment, this paper contrasts passive cooling systems with modern HVAC technologies, emphasizing their energy neutrality, low-carbon footprint, and long-term sustainability benefits. A SWOT analysis evaluates their strengths, limitations, opportunities for technological integration, and challenges posed by urbanization and regulatory constraints. This study adopts a comparative analytical method, integrating a literature-based approach with qualitative assessments and a SWOT analysis framework to evaluate passive cooling strategies against modern HVAC systems. Methodologically, the research combines historical review, typological classification, and sustainability-driven performance comparisons to derive actionable insights for climate-responsive design. The research is grounded in a comparative assessment of traditional and modern cooling strategies, supported by typological analysis and evaluative frameworks. Looking toward the future, the research explores hybrid adaptations incorporating solar energy, AI-driven airflow control, and retrofitting strategies for smart cities, reinforcing the enduring relevance of vernacular cooling techniques in contemporary architecture. By bridging historical knowledge with innovative solutions, this paper contributes to ongoing discussions on climate-responsive urban planning and sustainable architectural development.
]]>Authors: Ahmed M. Agwa Mamdouh I. Elamy
Recordings of wind velocity and associated wind turbine (WT) power possess noise, owing to inaccurate sensor measurements, atmosphere conditions, working stops, and flaws. The measurements still contain noise even after purification, so the fit curve of the wind turbine power might be different from the datasheet. The model of wind turbine power (MWTP) is significant, owing to its utilization for predicting and managing the wind energy. There are two types of MWTP, namely the parametric and the non-parametric types. Parameter identification of the parametric MWTP can be treated as a high nonlinear optimization problem. The fitness function is to minimize the root average squared errors (RASEs) between the calculated and measured wind powers while subject to a set of parameter constraints. The non-parametric MWTP is identified through training through machine learning. In this article, machine learning, namely the support vector regression (SVR), is innovatively applied for the identification of the non-parametric MWTP. Additionally, the dynamic force and the eigen parameters of WTs at different wind velocities are studied theoretically. The theoretical model for analyzing the natural frequencies of WT is validated using two techniques, namely the finite element method and the Euler–Bernoulli beam theory. The simulations are executed using MATLAB. The SVR is assessed via the comparison of its results with those of three parametric MWTP, viz. the 5-, 6-parameter logistic functions, and the modified hyperbolic tangent. It can be affirmed that the SVR execution is excellent and can produce the non-parametric MWTP with a RASE less than other algorithms by 0.4% to 93.8%, with a small computation cost.
]]>Authors: Anesu Godfrey Chitura Patrick Mukumba Ngwarai Shambira
Residential areas are characterized by closely packed buildings which disturb wind flow resulting in low wind speeds (below 2 m/s) with a high turbulence intensity (above 20%). In order to interface between off-the-shelf wind turbines and low-quality wind, the Increased velocity (INVELOX) wind delivery system is an attractive wind augmentation option for such regions. The INVELOX setup can harness more energy than conventional bare wind turbines under the same incident wind conditions. However, these systems also have drawbacks and challenges that they face in their operation, which amplify the need to review, understand, and expose gaps and flaws in pursuit of increased power production in low wind quality environments. This paper seeks to review and simplify the advances done by various scholars towards improving the INVELOX delivery system. It provides the mathematical foundation on which these advances are rooted and gives an understanding of how the improvements better the geometric properties of INVELOX. The article concludes by proposing future research directions.
]]>Authors: Zhihong Jiang Han Li Hao Yang Han Wu Wenzhou Liu Zhe Chen
This paper reviews the applications of artificial intelligence (AI) in the design optimization of wind power systems, mainly including (1) wind farm layout optimization; (2) wind turbine design optimization; and (3) wind farm electrical system design optimization. Firstly, this paper introduces the general considerations in the optimal design of wind power systems and the AI methods commonly used for the optimal design of wind power systems. Then the applications of AI in the optimal design of wind farms are reviewed in detail. Finally, further research directions of using AI methods in the optimal design of wind power systems are recommended.
]]>Authors: Taro Maruo Teruo Ohsawa
Accurate wind resource assessment is essential for offshore wind energy development, particularly in nearshore sites where atmospheric stability and internal boundary layers significantly influence the horizontal wind distribution. In this study, we investigated wind estimation methods using a high-resolution, 100 m grid Weather Research and Forecasting (WRF) model and coastal onshore wind measurement data. Five estimation methods were evaluated, including a control WRF simulation without on-site measurement data (CTRL), observation nudging (NDG), two offline methods—temporal correction (TC) and the directional extrapolation method (DE)—and direct application of onshore measurement data (DA). Wind speed and direction data from four nearshore sites in Japan were used for validation. The results indicated that TC provided the most accurate wind speed estimate results with minimal bias and relatively high reproducibility of temporal variations. NDG exhibited a smaller standard deviation of bias and a slightly higher correlation with the measured time series than CTRL. DE could not reproduce temporal variations in the horizontal wind speed differences between points. These findings suggest that TC is the most effective method for assessing nearshore wind resources and is thus recommended for practical use.
]]>Authors: Luis Arribas Javier Domínguez Michael Borsato Ana M. Martín Jorge Navarro Elena García Bustamante Luis F. Zarzalejo Ignacio Cruz
The deployment of utility-scale hybrid wind–solar PV power plants is gaining global attention due to their enhanced performance in power systems with high renewable energy penetration. To assess their potential, accurate estimations must be derived from the available data, addressing key challenges such as (1) the spatial and temporal resolution requirements, particularly for renewable resource characterization; (2) energy balances aligned with various business models; (3) regulatory constraints (environmental, technical, etc.); and (4) the cost dependencies of the different components and system characteristics. When conducting such analyses at the regional or national scale, a trade-off must be achieved to balance accuracy with computational efficiency. This study reviews existing experiences in hybrid plant deployment, with a focus on Spain, identifying the lack of national-scale product cost models for HPPs as the main gap and establishing a replicable methodology for hybrid plant mapping. A simplified example is shown using this methodology for a country-level analysis.
]]>Authors: Lusha M. Tronstad Michelle Weschler Amy Marie Storey Joy Handley Bryan P. Tronstad
Knowledge of how wind turbines interact with vertebrate animals is growing rapidly; however, less is known about plants and insects. Turbines produce infrasound (≤20 Hz), and these vibrations decrease with distance from turbines. We measured seed set and pollinators at six sites 0 to 28 km from turbines. We measured the number and mass of seeds produced by self-pollination, insect pollination, and when pollen was not limiting for nine native plants. We assessed pollinators by target netting bees and butterflies during transects, and by using blue vane traps (bees only). Most plants produced fewer or lighter developed seeds through self-pollination. Seed set did not vary between the open- and hand-pollinated treatments, indicating that the pollen was not limiting. The number and mass of seeds in the self-pollination treatment decreased with distance from the turbines. Bees and butterflies were more abundant near the wind facility, based on transects. The vane traps collected the fewest insects within the wind facility, likely due to bees being attracted to the turbine bases. The pollinator assemblage at the wind facility was distinct compared to other sites. Infrasound produced by the turbines appeared to enhance self-pollination, and the turbine bases attracted pollinators. We provide data on a seldom studied yet critical topic to inform land management and agricultural decisions, and to promote new strategies as wind energy development grows.
]]>Authors: Fedora Dias Anant Naik
Wind energy is a renewable energy resource that can be harnessed to generate electrical energy. In this paper, a novel Artificial Neural Network (ANN) approach using wavelet analysis for wind energy forecasting is proposed and tested with wind data from Kanyakumari, India, for different seasons. The wavelet decomposition is used to decom-pose the wind power time series data into different frequency components. The model simulates the complex mapping of historical wind power to allow the forecasting of wind power data for the next 3 h or the next 24 h. The predicted components are then reconstructed to obtain the overall predicted wind energy time series. The proposed models give more promising prediction results than the model without the use of wavelets. The regression coefficient and Mean Square Error (MSE) are computed and observed in order to assess the model’s performance.
]]>Authors: Raúl Sánchez-García Roberto Gómez-Martínez
The estimation of the aerodynamic characteristics of a rough surface (zero displacement plane d0 and aerodynamic roughness length z0) is important in the simulation of atmospheric boundary layer wind in a wind tunnel, since they are parameters involved in various problems of meteorological and wind engineering activities. In this study, morphometric methods were used to present parameterizations of d0 and z0 as functions of roughness and areal density based on wind tunnel measurements of airflow over a rough surface. Vertical profiles of mean wind speed, turbulence intensity, boundary layer depth, and spectral density functions are presented.
]]>Authors: Takuto Matsui Kazuki Matsuoka Kazuo Yamamoto
There have been numerous reported accidents of lightning strikes damaging wind turbine blades, which poses a serious problem. In certain accidents, the blades that were struck by lightning continued to rotate, resulting in breakage due to centrifugal force. Considering this background, wind turbines situated in Japan have been mandated to be equipped with emergency stop devices. Consequently, upon detection of a lightning strike by the device installed on the wind turbine, the turbine is promptly stopped. In order to restart the wind turbine, it is necessary to verify its soundness by conducting a visual inspection. However, conducting prompt inspections can be difficult due to various factors, including inclement weather. Therefore, this process prolongs the downtime of wind turbines and reduces their availability. In this study, an approach was proposed: a SCADA data analysis method using an autoencoder to assess the soundness of wind turbines without visual inspection. The present method selected wind speed and rotational speed as effective features, employing a sliding window for pre-processing, based on previous studies. Besides, the assessment of a trained autoencoder was conducted through the utilization of the confusion matrix and the receiver operating characteristic curve. It was suggested that the availability of wind turbines could be improved by employing this proposed method to remotely and automatically verify the soundness after lightning detection.
]]>Authors: James Naylor Qin Qin
Ground roughness is investigated for its influence on the propagation of wind turbine noise by using a proposed multiple scattering theory to predict the reflection of sound waves from a deterministic distribution of hemispheres. By using a distribution of hemispheres as an approximation for a realistic rough ground, a semi-analytical formulation for the reflected sound pressure is possible. Experiments are conducted within the University of Hull’s anechoic chamber and the results are compared against predictions from the proposed theory. Good agreement between the results is shown. The proposed multiple scattering theory also gives results consistent with a three-dimensional boundary element method, while having significantly shorter computation times and smaller memory requirements. Furthermore, results remain accurate up to the point where the radii of the hemispheres are comparable to the wavelengths of interest, which means that the scattering effect can be investigated more completely. When the proposed theory was applied to the unique source–receiver geometry of a wind turbine and a human height receiver, the excess attenuation calculated over an array of receivers showed significant fluctuations in sound pressure which were attributed to the ground roughness. Further works aim to incorporate weak refraction effects and ground absorption to analyze the relative influence of different parameters.
]]>Authors: Luca Caracoglia
This study examines output energy and efficiency of a torsional flutter harvester in gusty winds. The proposed apparatus exploits the torsional flutter of a rigid flapping foil, able to rotate about a pivot axis located in the proximity of the windward side. The apparatus operates at the “meso-scale”; i.e., the apparatus’ projected area is equal to a few square meters. It has unique properties in comparison with most harvesting devices and small wind turbines. The reference geometric chord length of the flapping foil is about one meter. Energy conversion is achieved by an adaptable linkage connected to a permanent magnet that produces eddy currents in a multi-loop winding coil. Operational conditions and the post-critical flutter regime are investigated by numerical simulations. Several configurations are examined to determine the output power and to study the effects of stationary turbulent flows on the energy-conversion efficiency. This paper is a continuation of recent studies. The goal is to examine the operational conditions of the apparatus for a potentially wide range of applications and moderate mean wind speeds.
]]>Authors: Claudia Roberta Calidonna Arijit Dutta Francesco D’Amico Luana Malacaria Salvatore Sinopoli Giorgia De Benedetto Daniel Gullì Ivano Ammoscato Mariafrancesca De Pino Teresa Lo Feudo
Accurate near-surface wind speed and direction measurements are crucial for validating atmospheric models, especially for the purpose of adequately assessing the interactions between the surface and wind, which in turn results in characteristic vertical profiles. Coastal regions pose unique challenges due to the discontinuity between land and sea and the complex interplay of atmospheric stability, topography, and boundary/layer dynamics. This study focuses on a unique database of wind profiles collected over several years at a World Meteorological Organization—Global Atmosphere Watch (WMO/GAW) coastal site in the southern Italian region of Calabria (Lamezia Terme, code: LMT). By leveraging remote sensing technologies, including wind lidar combined with in situ measurements, this work comprehensively analyzes wind circulation at low altitudes in the narrowest point of the entire Italian peninsula. Seasonal, daily, and hourly wind profiles at multiple heights are analyzed, highlighting the patterns and variations induced by land–sea interactions. A case study integrating Synthetic Aperture Radar (SAR) satellite images and in situ observations demonstrates the importance of multi-sensor approaches in capturing wind dynamics and validating model simulations. Data analyses demonstrate the occurrence of extreme events during the winter and spring seasons, linked to synoptic flows; fall seasons have variable patterns, while during the summer, low-speed winds and breeze regimes tend to prevail. The prevailing circulation is of a westerly nature, in accordance with other studies on large-scale flows.
]]>Authors: Qiang Lin Naoko Konno Hideyuki Tanaka Qingshan Yang Yukio Tamura
Wind speed increases in pedestrian-level spaces around high-rise buildings tend to cause uncomfortable and even unsafe wind conditions for pedestrians. Especially, instantaneous strong winds can have a significant impact on the body sensation of pedestrians, and they are usually related to complex flow patterns around buildings. A detailed examination of flow patterns corresponding to instantaneous strong wind events around high-rise buildings is essential to understanding the physical mechanism of this phenomenon. To quantitatively evaluate the pedestrian-level wind environment around high-rise buildings, two important indices, speed-up ratio and speed-up area, have usually been introduced. In this study, a Large Eddy Simulation (LES) was conducted for square-section building models with different heights, represented by H (=100 m, 200 m, and 400 m in full-scale) or aspect ratios, represented by H/B0 (=2, 4, and 8), where B0 (=50 m in full-scale) represents the building width. Two instantaneous strong wind events providing a “maximum speed-up ratio” and a “maximum speed-up area” of pedestrian-level wind are investigated based on a conditional average method. The results indicate that these two instantaneous strong wind events usually do not occur simultaneously. Flow patterns around buildings for the two events are also different: the contribution of downwash tends to be larger for strong wind events providing “maximum speed-up area” showing more three-dimensional characteristics.
]]>Authors: Xsitaaz T. Chadee Naresh R. Seegobin Ricardo M. Clarke
Many Caribbean low-latitude small island states lack wind maps tailored to capture their wind features at high resolutions. However, high-resolution mesoscale modeling is computationally expensive. This study proposes a statistical–dynamical downscaling (SDD) method that integrates an atmospheric-circulation-type (CT) approach with a high-resolution numerical weather prediction (NWP) model to map the wind resources of a case study, Trinidad and Tobago. The SDD method uses a novel wind class generation technique derived directly from reanalysis wind field patterns. For the Caribbean, 82 wind classes were defined from an atmospheric circulation catalog of seven types derived from 850 hPa daily wind fields from the NCEP-DOE reanalysis over 32 years. Each wind class was downscaled using the Weather Research and Forecasting (WRF) model and weighted by frequency to produce 1 km × 1 km climatological wind maps. The 10 m wind maps, validated using measured wind data at Piarco and Crown Point, exhibit a small positive average bias (+0.5 m/s in wind speed and +11 W m−2 in wind power density (WPD)) and capture the shape of the wind speed distributions and a significant proportion of the interannual variability. The 80 m wind map indicates from good to moderate wind resources, suitable for determining priority areas for a detailed wind measurement program in Trinidad and Tobago. The proposed SDD methodology is applicable to other regions worldwide beyond low-latitude tropical islands.
]]>Authors: Hamidreza Abedi Claes Eskilsson
Wind power plays an increasingly vital role in sustainable energy development. However, accurately simulating wind turbine aerodynamics, particularly in offshore wind farms, remains challenging due to complex environmental factors such as the marine atmospheric boundary layer. This study investigates the integration and assessment of the Actuator Line Model (ALM) within the high-order spectral/hp element framework, Nektar++, for wind turbine aerodynamic simulations. The primary objective is to evaluate the implementation and effectiveness of the ALM by analyzing aerodynamic loads, wake behavior, and computational demands. A three-bladed NREL-5MW turbine is modeled using the ALM in Nektar++, with results compared against established computational fluid dynamics (CFD) tools, including SOWFA and AMR-Wind. The findings demonstrate that Nektar++ effectively captures velocity and vorticity fields in the turbine wake while providing aerodynamic load predictions that closely align with finite-volume CFD models. Furthermore, the spectral/hp element framework exhibits favorable scalability and computational efficiency, indicating that Nektar++ is a promising tool for high-fidelity wind turbine and wind farm aerodynamic research.
]]>Authors: Akarsh Gupta Yashwant Kashyap Panagiotis Kosmopoulos
This paper explores the potential of Airborne Wind Energy Systems to revolutionize wind energy generation, demonstrating advancements over current methods. Through a series of controlled field experiments and the application of classical machine learning techniques, we achieved significant improvements in tether force estimation. Our XGBoost model, for example, demonstrated a notable reduction in error in predicting the tether force that can be extracted at a particular location, with a root mean square error of 52.3 Newtons and a mean absolute error of 32.1 Newtons, coupled with a R2 error, which measures the proportion of variance explained by the model, achieved an impressive value of 0.93. These findings not only validate the effectiveness of our proposed methods but also illustrate their potential to optimize the deployment of Airborne Wind Energy Systems, thereby maximizing energy output and contributing to a sustainable, low-carbon energy future. By analyzing key input features such as wind speed and kite dynamics, our model predicts optimal locations for Airborne Wind Energy System installation, offering a promising alternative to traditional wind turbines.
]]>Authors: Ali Aranizadeh Mirpouya Mirmozaffari Behnam Khalatabadi Farahani
Wind power output fluctuations, driven by variable wind speeds, create significant challenges for grid stability and the efficient use of wind turbines, particularly in high-wind-penetration areas. This study proposes a combined approach utilizing an ultra-capacitor energy storage system and fuzzy-control-based pitch angle adjustment to address these challenges. The fuzzy control system dynamically responds to wind speed variations, optimizing energy capture while minimizing mechanical stress on turbine components, and the ultra-capacitor provides instantaneous buffering of power surpluses and deficits. Simulations conducted on a 50 kW DFIG wind turbine powering a 23 kW load demonstrated a substantial reduction in power fluctuations by a factor of 3.747, decreasing the power fluctuation reduction scale from 13.04% to 3.48%. These results highlight the effectiveness of the proposed system in improving the stability, reliability, and quality of wind energy, thereby advancing the broader adoption of renewable energy and contributing to sustainable energy solutions.
]]>Authors: Peter Kinsley Sam Porteous Stephen Jones Priyan Subramanian Olga Campo Kirsten Dyer
Blade leading edge erosion (LEE) is a persistent challenge in the wind industry, resulting in reduced aerodynamic efficiency and increased maintenance costs, with an estimated total expense of GBP 1.3M over a 25-year turbine lifetime. To mitigate these effects, leading edge protection (LEP) systems are widely used, but their real-world performance often falls short of predictions based on the standard rain erosion test (RET). This study investigates the limitations of current RET practices, which are designed to accelerate testing but fail to replicate the diverse environmental conditions experienced by wind turbines. Two LEPs with contrasting viscoelastic properties were tested using a novel design of experiments (DoEs) approach. The study explored the droplet impact frequency, combination and sequencing of high or low rainfall intensities, recovery during the inspection period and droplet size effects on erosion behaviour, to uncover significant differences in material performance compared to standard RET conditions. Results, supported by dynamic mechanical analysis (DMA), indicated that the chosen LEPs undergo a transition between elastic and brittle failure modes at a critical impact frequency, influenced by the viscoelastic properties of the material. Importantly, the findings emphasise the need for revised testing protocols across a range of parameters that incorporate realistic environmental conditions to improve the predictability of LEP performance.
]]>Authors: Faith Nobert Tim Weis Andrew Leach Sergi Arús García
The introduction of a significant industrial carbon price in Alberta, Canada, has precipitated major changes in its electricity market, both for fossil fuel generators, which has resulted in a rapid transition from coal to natural gas, as well as for renewable energy projects, which can monetize emission offset credits. Coal, which generated close to half of the electricity in the province in 2016 before the major changes were introduced, had fallen to less than 8 percent by the end of 2023 and was completely phased out by June 2024. Conversely, wind energy grew from 6 to 12 percent of the annual supply, in part due to the increasing value of the carbon credits whose value is connected to the deemed greenhouse emissions they are displacing. As wind energy increased in penetration, it lowered its own market price, which was discounted from the average market price by 10–43 percent, but in turn increased the relative importance of its offset. This paper examines the evolution of emissions displaced by wind energy in Alberta by considering 10 years of historical merit order data and creating a counterfactual scenario where historical wind generation is replaced by next-in-merit units. On average, coal made up 84 percent of the marginal energy and 93 percent of the marginal emissions in 2018. As the coal capacity declined, natural gas units replaced coal on the margins, jumping from 21 percent of next-in-merit generation in 2020 to 84 percent in 2023. Alberta uses a deemed emissions displacement factor, which is a combination of historical build and operating margins that declined from 0.65 tCO2e/MWh in 2010 to 0.52 tCO2e/MWh in 2023. Using the counterfactual scenario, an alternative offset value is considered, which had a maximum difference of 57 percent (9 CAD/MWh) of increased value over the actual historical offset. However, the counterfactual rate of emission offsets fell to near parity with the deemed grid displacement factor by 2022 as natural gas became increasingly dominant in the market. As the carbon price is scheduled to increase from 65 CAD/tCO2e in 2023 to 170 CAD/tCO2e by 2030, the provincial offset could reach a maximum value of 53 CAD/MWh in 2030 but begin to decline thereafter as the carbon price drives decarbonization, thereby lowering displaced emissions in either method of calculation. The introduction of significant carbon pricing into a thermally dominated electricity market resulted in more emissions being displaced by renewable energy than they were credited for in the short term, but the resultant decarbonization of the grid decreases the long-term value of emission offsets.
]]>Authors: Mareike Leimeister
The current technological developments within the offshore wind industry reveal a trend towards larger wind turbine MW-classes for both bottom-fixed and floating support structures. Furthermore, bottom-fixed designs are modified and enhanced to also serve deeper offshore sites. Apart from these technological developments, another trend of a competitive nature, related to politics and other stakeholders, can be observed: ever-higher targets are specified for offshore wind energy, while national offshore water areas are limited and divided among various stakeholders in terms of their use. This situation raises the following questions, which are discussed in this paper: 1. Should and could floating offshore wind be extended to shallow-water regions? 2. What benefits can be gained when going beyond traditional floating wind technologies, and what does this mean in detail? 3. What are the motivations, challenges, and solutions for coexistence options? The investigations reveal that floating solutions are more than just options for supporting offshore wind turbines at very-deep-water sites. By extending the traditional application ranges of floating wind turbine systems and going beyond traditional floating offshore wind technologies, additional benefits can be reaped, and worldwide climate and renewable energy targets can be met in harmony with other stakeholders.
]]>Authors: Gabriel Narancio Djordje Romanic Jubayer Chowdhury Han-Ping Hong Horia Hangan
In this study, the loads induced by tornado-like vortices on scaled models of eight low-rise residential buildings with real-world shapes in a typical North American community are quantified and compared to the provisions provided by ASCE/SEI 7–22. Physical simulations of the interaction between translating tornado-like vortices representative of EF1-, EF2- and EF3-rated tornadoes and the scaled models were performed in the WindEEE Dome at the University of Western Ontario. Three internal pressure scenarios were numerically simulated. The tornado velocity gust factor was identified as a critical parameter when translating loads from the model to full-scale. The uplift forces on the whole roof in the internal pressure scenarios with one dominant opening are between 44% and 63% higher than the distributed leakage scenario, highlighting the importance of keeping the integrity of the envelope. Revised values of the internal pressure coefficients and external pressure coefficients or correction factors may be used to improve the ability of the standard to provide safer design loads.
]]>Authors: Abdulwahab Rawesat Pericles Pilidis
This paper offers a basic analysis for strategic decision-makers of the process when an economy shifts from oil to non-carbon energy exports and zero carbon emissions. The fundamental concept is how to offer environmental performance without causing an economic contraction. The costs and feasibility of solar, wind, and helium closed-cycle technologies are thoroughly and independently compared. Solar panels make up 0.67% of the USD 1.14 trillion total cost of solar energy, which is the capital investment, with panels accounting for 0.51%. Future technical developments are expected to bring down the cost of such solar farms to USD 0.74 trillion. Turbines comprise 66% of the estimated USD 0.67 trillion wind energy costs. At USD 0.36 trillion, helium closed-cycle gas turbines—which account for 0.78% of the overall cost—are essential for stabilising energy output. With a focus on cost viability, this analysis offers direction for Libya’s transition to energy self-sufficiency and export, in support of global carbon reduction targets. It also offers unique insights into areas not previously covered by other studies. This paper’s unique contribution is its economic analysis of the decarbonisation of an entire oil-exporting nation.
]]>Authors: Glib Ivanov Kai-Tung Ma
The increasing demand for cost-effective floating offshore wind turbines (FOWTs) necessitates streamlined mass production and efficient assembly strategies. This research investigates the assembly and integration of 15 MW FOWT floaters, utilising a semi-submersible floater equipped with a 15 MW wind turbine. The infrastructure and existing port facilities of Taiwan are used as an example. The effectiveness of various assembly and integration strategies has been evaluated. The study outlines equipment and infrastructure requirements for on-quay floater and turbine assembly, comparing on-quay assembly to construction at remote locations and subsequent towing. Detailed analyses of port operations, crane specifications, and assembly procedures are presented, emphasising the critical role of crane selection and configuration. The findings indicate that on-quay assembly at one major port is feasible and cost-effective, provided that port infrastructure and operational logistics are optimised. This research offers insights and recommendations for implementing large-scale FOWT projects, contributing to advancing offshore wind energy deployment.
]]>Authors: James Naylor Qin Qin
In an investigation into how wind turbine noise interacts with the surrounding terrain, its propagation over rough ground is simulated using a parabolic equation code using a modified effective impedance model, which characterizes the effects of a three-dimensional, rigid roughness within a relatively long wavelength limit (ka≤1). The model is validated by comparison to experiments conducted within an anechoic chamber wherein different source–receiver geometries are considered. The relative sound pressure level spectra from the parabolic equation code using the modified effective impedance model highlight a sensitivity to the roughness parameters. At a low frequency and far distance, the relative sound pressure level decreased as the roughness coverage increased. A difference of 4.9 dB has been reported. The simulations highlight how the roughness shifts the ground effect dips, resulting in the sound level at the distance of 2 km being altered. However, only the monochromatic wave has been discussed. Further work on broadband noise is desirable. Furthermore, due to the long wavelength limit, only a portion of audible wind turbine noise can be investigated.
]]>Authors: Altan Unlu Malaquias Peña
Climate change is increasing the occurrence of extreme weather events, such as intense windstorms, with a trend expected to worsen due to global warming. The growing intensity and frequency of these events are causing a significant number of failures in power distribution grids. However, understanding the nature of extreme wind events and predicting their impact on distribution grids can help and prevent these issues, potentially mitigating their adverse effects. This study analyzes a structured method to predict distribution grid disruptions caused by extreme wind events. The method utilizes Machine Learning (ML) models, including K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Machine (SVM), Decision Trees (DTs), Gradient Boosting Machine (GBM), Gaussian Process (GP), Deep Neural Network (DNN), and Ensemble Learning which combines RF, SVM and GP to analyze synthetic failure data and predict power grid outages. The study utilized meteorological information, physical fragility curves, and scenario generation for distribution systems. The approach is validated by using five-fold cross-validation on the dataset, demonstrating its effectiveness in enhancing predictive capabilities against extreme wind events. Experimental results showed that the Ensemble Learning, GP, and SVM models outperformed other predictive models in the binary classification task of identifying failures or non-failures, achieving the highest performance metrics.
]]>Authors: Stylianos Hadjipetrou Phaedon Kyriakidis
Wind speed (and direction) estimated from numerical weather prediction (NWP) models is essential to wind energy applications, especially in the absence of reliable fine scale spatio-temporal wind information. This study evaluates four high-resolution wind speed numerical datasets (UERRA MESCAN-SURFEX, CERRA, COSMO-REA6, and NEWA) against in situ observations from coastal meteorological stations in the eastern Mediterranean basin. The evaluation is based on statistical comparisons of long-term wind speed data from 2009 to 2018 and involves an in-depth statistical comparison as well as a preliminary wind power density assessment at or near the meteorological station locations. The results show that while all datasets provide valuable insights into regional wind variability, there are notable differences in model performance. COSMO-REA6 and UERRA exhibit higher variability in wind speed but tend to underestimate extreme values, particularly in the southern coastal areas, whereas CERRA and NEWA provided closer fits to observed wind speeds, with CERRA showing the highest correlation at most stations. NEWA data, where available, overestimate average wind speeds but capture extreme values well. The comparison reveals that while all datasets provide valuable insights into the spatial and temporal variability of wind resources, their performance varies by location and season, emphasizing the need for the careful selection and potential calibration of these models for accurate wind energy assessments. The study provides essential groundwork for leveraging these datasets in planning and optimizing offshore wind energy projects, contributing to the region’s transition to renewable energy sources.
]]>Authors: Jagdeep Singh Jahrul M Alam
In large wind farms, the interaction of atmospheric turbulence and wind turbine wakes leads to complex vortex dynamics and energy dissipation, resulting in reduced wind velocity and subsequent loss of wind power. This study investigates the influence of vortex stretching on wind power fluctuations within wind turbine wakes using scale-adaptive large eddy simulation. The proper orthogonal decomposition method was employed to extract the most energetic contributions to the wind power spectra. Vertical profiles of mean wind speed, Reynolds stresses, and dispersive stresses were analyzed to assess energy dissipation rates. Our simulation results showed excellent agreement when compared with wind tunnel data and more advanced numerical models, such as the actuator line model and the actuator line model with hub and tower effects. This highlights the important role of coherent and energetic flow components in the spectral behavior of wind farms. The findings indicate a persistent energy cascading length scale in the wake of wind turbines, emphasizing the vertical transport of energy to turbine blades. These results complement existing literature and provide new insights into the dynamics of wind turbine wakes and their impact on wind farm performance.
]]>Authors: Arun Selvaraj Ganesh Mayilsamy
This paper presents the design and analysis of an efficient energy management system for a wind lens integrated with a permanent magnet synchronous generator (PMSG) and a zeta converter. The wind lens, a ring-shaped structure encircling the rotor, enhances the turbine’s capability to capture wind energy by increasing the wind influx through the turbine. In the contemporary wind energy sector, PMSGs are extensively employed due to their superior performance characteristics. This study integrates a 1 kW PMSG system with a wind lens to optimize power extraction from the wind energy conversion system (WECS) under varying wind speeds. A comparative analysis of different control strategies for maximum power point tracking (MPPT) is conducted, including the incremental conductance (INC) method and the perturb and observe (P&O) method. The performance of the MPPT controller integrated with the wind lens-based PMSG system is assessed based on output DC voltage and power delivered to the load. To evaluate the overall effectiveness of these control strategies, both steady-state voltage and dynamic response under diverse wind conditions are examined. The system is modeled and simulated using the MATLAB R2023a/Simulink 9.1 software, and the simulation results are validated to demonstrate the efficacy of the proposed energy management system.
]]>Authors: Federico Della Santa Gianluca Zorzi Ali Mehmanparast
Fatigue poses significant challenges for the structural integrity of monopiles, the most common type of foundation for offshore wind turbines. These structures are usually manufactured by rolling and welding together large steel plates. Offshore wind turbines are typically designed to operate for 20 years or longer, thus the number of cycles to failure (Nf) that these structures are required to withstand lies in the so called ultrahigh-cycle fatigue (UHCF) regime (Nf>108). Moreover, because, in the past few years, there has been a continuous increase in the size of monopiles, the fatigue life reduction caused by the utilization of thicker steel plates plays an important role (i.e., thickness or size effect). Different regions worldwide apply distinct codes to ensure that offshore structures can withstand fatigue damages, but most of them are tailored for the high-cycle fatigue (HCF) regime. This paper seeks to compare a selection of these codes, highlighting both differences and similarities, while also questioning their suitability in the UHCF regime and for much thicker structures (compared to the reference thickness values reported in the standards). By doing so, it aims to contribute to the ongoing efforts to optimize the efficiency of the fatigue life assessment of offshore wind infrastructures. The focus of this study is on double-V transverse butt welds and their S-N curves in air and seawater (with and without cathodic protection), while the analyzed standards are those provided by the Det Norske Veritas (DNV-RP-C203-2021), the British Standards Institution (BS 7608, including the amendments of 2015), and the European Union (EN 1993-1-9, updated in 2005). The results have been discussed in terms of the level of conservatism that each of these standards offers and in identifying the areas for further research to enable extended lives in the current and future offshore wind monopile foundations.
]]>Authors: Mário Vieira Dragan Djurdjanovic
The present research explores the optimization of maintenance strategies for floating offshore wind (FOW) farms using nested genetic algorithms. The primary goal is to provide insights on the decision-making processes required for both immediate and strategic maintenance planning, crucial for the viability and efficiency of FOW operations. A nested genetic algorithm was coupled with discrete-event simulations in order to simulate and optimize maintenance scenarios influenced by various operational and environmental parameters. The study revealed that short-term maintenance timing is significantly influenced by wind conditions, with higher electricity prices justifying on-site spare parts storage to mitigate operational disruptions, suggesting economic incentives for maintaining on-site inventory of spare parts. Long-term strategic findings emphasized the impact of planned intervals between inspections on financial outcomes, identifying optimal strategies that balance operational costs with energy production efficiency. Ultimately, this study highlights the importance of integrating sophisticated predictive models for failure detection with real-time operational data to enhance maintenance decision-making in the evolving landscape of offshore wind energy, where future farms are likely to operate farther from onshore facilities and under potentially highly varying market conditions in terms of electricity prices.
]]>Authors: Diego Manuel Chamorro Ruz Henrik C. Pedersen Jesper Liniger Mohit Bhola Gyan Wrat
Failures in hydraulic systems in offshore wind turbines represent an enormous challenge for manufacturers and operators, as the pitch system statistically is one of the subsystems contributing the most to the downtime of the turbines, which is the case for both electrical and hydraulic pitch systems. However, the complex failure mechanisms of the various different hydraulic components mean that, typically, the critical components of hydraulic systems must be tested to better understand the failure mechanisms. Nonetheless, conventional testing procedures are lengthy and costly. Accelerated testing plays a critical role as it can mimic hydraulic system failure mechanisms in a shorter period. However, the lack of standardized test methods and detailed knowledge about the failure-accelerating effects complicates the process. Therefore, this paper offers a comprehensive examination of approaches applicable to conducting accelerated tests on hydraulic systems. It identifies and discusses five primary component types or sub-components related to the acceleration of testing in hydraulic systems: pumps, cylinders, seals, valves, and hoses. Each section references studies that delve into accelerated testing methodologies for these individual components. Furthermore, within each component, a concise overview of the current techniques is provided, followed by a discussion and summary based on the state of the art.
]]>Authors: Alois Peter Schaffarczyk Brandon Arthur Lobo Nicholas Balaresque Volker Kremer Janick Suhr Zhongxia Wang
We designed 60% thick airfoil to improve the aerodynamic performance in the root region of wind turbine rotor blades, taking into account current constraints. After an extensive literature review and patent research, a design methodology (including the considerations of simple manufacturing) was set up, and extensive 2D- and 3D-CFD investigations with four codes (Xfoil, MSES, ANSYS fluent, and DLR-tau) were performed, including implementation inside a generic 10 MW test-blade (CIG10MW). Comparison with results from Blade Element Momentum (BEM) methods and the estimation of 3D effects due to the rotating blade were undertaken. One specific shape (with a pronounced flat-back) was selected and tested in the Deutsche WindGuard aeroacoustic Wind Tunnel (DWAA), in Bremerhaven, Germany. A total of 34 polars were measured, included two trailing edge shapes and aerodynamic devices such as vortex generators, gurney flaps, zig-zag tape, and a splitter plate. Considerable changes in lift and drag characteristics were observed due to the use of aerodynamic add-ons. With the studies presented here, we believe we have closed an important technological gap.
]]>Authors: Daniel Gonzalez-Delgado Pablo Jaen-Sola Erkan Oterkus
Generative design techniques together with the rapid development of additive manufacturing represent a revolution in the field of structural optimisation processes. In this study, a static structural and modal analysis was integrated to drive a multi-objective generative design optimisation process for a 3 MW direct-drive offshore wind turbine electrical generator rotor structure. This novel optimisation approach implements an automated fittest-for-purpose process including a static structural analysis and a modal analysis as the input for the optimisation strategy algorithm, allowing the exploration of a wide range of non-conventional topologies. If compared with the simple generator rotor disc structure, the results obtained using this innovative method achieved over 7% of weight reduction and a 39% increment in the generator operational range with the consequent growth in the wind turbine energy capture capability. Moreover, this approach generates a vast amount of structural analysis information, crucial at an early stage of the development of large-scale projects for a cost-effective scheme.
]]>Authors: Roland Fürbacher Gerhard Liedl Gabriel Grünsteidl Andreas Otto
Ice accumulation on lift-generating surfaces, such as rotor blades or wings, degrades aerodynamic performance and increases various risks. Active measures to counteract surface icing are energy-consuming and should be replaced by passive anti-icing surfaces. Two major categories of surface treatments—coating and structuring—already show promising results in the laboratory, but none fulfill the current industry requirements for performance and durability. In this paper, we show how femtosecond laser structuring of stainless steel (1.4301) combined with a hydrocarbon surface treatment or a vacuum treatment leads to superhydrophobic properties. The anti-ice performance was investigated in an icing wind tunnel under glaze ice conditions. Therefore, flexible steel foils were laser-structured, wettability treated and attached to NACA 0012 air foil sections. In the icing wind tunnel, hydrocarbon treated surfaces showed a 50 s ice build-up delay on the leading edge as well as a smoother ice surface compared to the reference. To demonstrate the erosion resistance of these surfaces, long-term field tests on a small-scale wind turbine were performed under alpine operating conditions. The results showed only minor erosion wear of micro- and nano-structures after a period of six winter months.
]]>Authors: Robert Lochhead Orla Donnelly James Carroll
With the current trends of wind energy already playing a major part in the Scottish energy supply, the capacity of wind farms is predicted to grow exponentially and reach further depths offshore. However, a key challenge that presents itself is the integration of large producing assets into the current UK grid. One potential solution to this is green hydrogen production, which is being heavily researched in industry, with many concepts being investigated for large-scale purposes. However, the operations and maintenance (O&M) costs and availability of green hydrogen systems need to be quantified to ensure economical and technical viability, which is sparse in the available literature. The study presented in this paper investigated the availability and O&M costs of coupled wind–hydrogen systems by attempting to quantify the failure rates, repair times, repair costs and number of technicians required for key green hydrogen components. This study also utilised an O&M model created by the University of Strathclyde, which uses Monte Carlo Markov chain simulations to produce the O&M outputs. A number of assumptions were made throughout the study in relation to the O&M model inputs, and the baseline availability for the coupled wind–hydrogen system was 85.24%. Whilst the wind turbine still contributed a major part to the downtime seen in the simulations, the combined hydrogen system also contributed a significant amount, a total of 37%, which could have been due to the technology readiness levels of some the components included in the hydrogen system.
]]>Authors: Glen Currie Edward Behrens Samuel Bolitho Michael Coen Thomas Wilson
The energy transition to wind and solar opens up opportunities for green hydrogen as wind and solar generation tend to bring electricity prices down to very low levels. We evaluate whether green hydrogen can integrate well with wind and solar PVs to improve the South Australian electricity grid. Green hydrogen can use membrane electrolysis plants during periods of surplus renewable energy. This hydrogen can then be electrified or used in industry. The green hydrogen system was analysed to understand the financial viability and technical impact of integrating green hydrogen. We also used system engineering techniques to understand the system holistically, including the technical, social, environmental, and economic impacts. The results show opportunities for the system to provide seasonal storage, grid firming, and reliability services. Financially, it would need changes to electricity rules to be viable, so at present, it would not be viable without subsidy.
]]>Authors: Onofre Morfín Diego Delgado Alan Campos Miguel Murillo Jesús I. Hernández Pedro Esquivel
Wind systems are sustainable and economical options for producing electrical energy. These systems efficiently manage the power flow by maximizing wind power and consuming reactive power from the grid. In addition, wind systems must maintain operation despite utility grid electrical failure; hence, their control system must not collapse. This study proposes a fault-tolerant converter controller to ensure the efficient operation of wind system converters. The central concept behind this is that when there is an imbalance in the utility grid voltage due to a fault nearby or far away, positive and negative sequence voltages are created in the time domain. Then, two parallel controllers operate to allow the wind system to continue operating despite the failure. One controller utilizes positive sequence voltages as inputs to regulate the generator’s electromagnetic torque. This helps in maximizing the amount of wind energy. The second controller uses negative sequence voltages as inputs, which helps to cancel out the produced torque in the opposite direction, thereby preventing generator overload. Finally, the controllers proposed in this article are validated through simulations, and the results are presented.
]]>Authors: Maria Margarita Bertsiou Evangelos Baltas
The necessity for transitioning to renewable energy sources and the intermittent nature of the natural variables lead to the integration of storage units into these projects. In this research paper, wind turbines and solar modules are combined with pumped hydro storage, batteries, and green hydrogen. Energy management strategies are described for five different scenarios of hybrid renewable energy systems, based on single or hybrid storage technologies. The motivation is driven by grid stability issues and the limited access to fresh water in the Greek islands. A RES-based desalination unit is introduced into the hybrid system for access to low-cost fresh water. The comparison of single and hybrid storage methods, the exploitation of seawater for the simultaneous fulfillment of water for domestic and agricultural purposes, and the evaluation of different energy, economic, and environmental indices are the innovative aspects of this research work. The results show that pumped hydro storage systems can cover the energy and water demand at the minimum possible price, 0.215 EUR/kWh and 1.257 EUR/m3, while hybrid storage technologies provide better results in the loss of load probability, payback period and CO2 emissions. For the pumped hydro–hydrogen hybrid storage system, these values are 21.40%, 10.87 years, and 2297 tn/year, respectively.
]]>Authors: Khathutshelo Steven Sivhugwana Edmore Ranganai
Considering that wind power is proportional to the cube of the wind speed variable, which is highly random, complex power grid management tasks have arisen as a result. Wind speed prediction in the short term is crucial for load dispatch planning and load increment/decrement decisions. The chaotic intermittency of speed is often characterised by inherent linear and nonlinear patterns, as well as nonstationary behaviour; thus, it is generally difficult to predict it accurately and efficiently using a single linear or nonlinear model. In this study, wavelet transform (WT), autoregressive integrated moving average (ARIMA), extreme gradient boosting trees (XGBoost), and support vector regression (SVR) are combined to predict high-resolution short-term wind speeds obtained from three Southern African Universities Radiometric Network (SAURAN) stations: Richtersveld (RVD); Central University of Technology (CUT); and University of Pretoria (UPR). This hybrid model is termed WT-ARIMA-XGBoost-SVR. In the proposed hybrid, the ARIMA component is employed to capture linearity, while XGBoost captures nonlinearity using the wavelet decomposed subseries from the residuals as input features. Finally, the SVR model reconciles linear and nonlinear predictions. We evaluated the WT-ARIMA-XGBoost-SVR’s efficacy against ARIMA and two other hybrid models that substitute XGBoost with a light gradient boosting machine (LGB) component to form a WT-ARIMA-LGB-SVR hybrid model and a stochastic gradient boosting machine (SGB) to form a WT-ARIMA-SGB-SVR hybrid model. Based on mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), coefficient of determination (R2), and prediction interval normalised average width (PINAW), the proposed hybrid model provided more accurate and reliable predictions with less uncertainty for all three datasets. This study is critical for improving wind speed prediction reliability to ensure the development of effective wind power management strategies.
]]>Authors: Alexandra C. Barmpatza Remi Peltier Constantinos Condaxakis Dimitris Christakis
This article investigates the construction of a wind power generator requiring the lowest possible cost. The proposed model is an Axial Flux Permanent Magnet (AFPM) Synchronous Machine, which contains two iron rotors and a coreless stator between them, constructed from resin. The scientific contribution relates to the coupling of economic and technical parameters, which will clarify the feasibility, i.e., a wind turbine construction capable of producing approximately 3.5 KW, using a simple mill and a generator of nominal rotor speed 100 rpm. Such studies are few in international literature and mainly concern low levels of rotor speed in relation to the produced output power. For the generator dimensioning, analytical equations are used, while the type and the dimensions of the magnets are determined, before the start of dimensioning. The authors carried out research in the international market, ending up with specific cost-effective magnets, while trying to adjust the remaining dimensions and materials of the machine based on these cost-effective magnets and the aforementioned nominal values of the generator. The machine, whose dimensions are derived by analytical equations, was simulated and analyzed using the Two-Dimensional Finite Element Method (2D-FEM) and the Three-Dimensional Finite Element Method (3D-FEM), for comparison purposes. Moreover, an economic analysis of the generator and its individual parts was conducted. Finally, a novel idea for reducing the total generator cost is proposed, by replacing the rotor disks with rings. The investigation revealed that analytical equations can predict with satisfactory accuracy the generator’s parameters. In addition, as permanent magnets are the most expensive materials in the construction, their predetermination using low-cost magnets can reduce the construction cost. Finally, the proposed concept of a ring-shaped rotor instead of a disk rotor, provides a cost reduction of up to 20%.
]]>Authors: Saeid Fadaei Fred F. Afagh Robert G. Langlois
The emerging industry of offshore wind turbines mounted on floating bases has garnered significant attention from both academia and industry. The desire to understand the complex physics of these floating structures has led to the development of numerical and physical modelling techniques. While physical testing has traditionally been employed, there is a growing focus on cost-effective and accurate high-fidelity numerical modelling as a potential alternative or supplement. However, commonly used numerical engineering tools in the offshore industry are considered mid- to low-fidelity and may lack the desired precision for floating offshore wind turbines (FOWTs). Given the complexity of these simulation codes, it is crucial to validate their accuracy. To address this, the International Energy Agency (IEA) Wind Technology Collaboration Programme initiated various research endeavors, including the Offshore Code Comparison Collaboration (OC3), Offshore Code Comparison Collaboration Continuation (OC4), Offshore Code Comparison Collaboration Continuation with Correlation (OC5), and the recent Offshore Code Comparison Collaboration Continued with Correlation and Uncertainty (OC6) projects. This study offers a comprehensive survey of the simulation tools available for FOWTs which were part of OC projects, focusing particularly on horizontal axis wind turbines (HAWTs) and highlighting their capabilities and fundamental theories.
]]>Authors: Arthur Harger Lucas H. S. Carmo Alfredo Gay Neto Alexandre N. Simos Guilherme R. Franzini Guilherme Henrique Rossi Vieira
One of the sources of sustainable energy with great, still untapped potential is wind power. One way to harness such potential is to develop technology for offshore use, more specifically at high depths with floating turbines. It is always critical that their structural designs guarantee that their natural frequencies of vibration do not match the frequencies of the most important oscillatory loads to which they will be subjected. This avoids resonance and its excessive undesired oscillatory responses. Based on that, a 3D finite element model of a 15 MW semi-submersible floating offshore wind turbine was developed in the commercial software ANSYS Mechanical ® to study its dynamic behavior and contribute to the in-depth analysis of structural modeling of FOWTs. A tower and floating platform were individually modeled and coupled together. The natural frequencies and modes of vibration of the coupled system and of its components were obtained by modal analysis, not only to verify the resonance, but also to investigate the determinant factors affecting such behaviors, which are not extensively discussed in literature. It was found that there is strong coupling between the components and that the tower affects the system as a result of its stiffness, and the floater as a result of its rotational inertia. The platform’s inertia comes mainly from the ballast and the effects of added mass, which was considered to be a literal increase in mass and was modeled in two manners: first, it was approximately calculated and distributed along the submerged flexible platform members and then as a nodal inertial element with the floater being considered as a rigid body. The second approach allowed an iterative analysis for non-zero frequencies of vibration, which showed that a first approximation with an infinite period is sufficiently accurate. Furthermore, the effects of the mooring lines was studied based on a linear model, which showed that they do not affect the boundary conditions at the bottom of the tower in a significant way.
]]>Authors: Zhe Chen
Wind power, as a vital renewable power source, has undergone rapid developments in recent years [...]
]]>Authors: Sung Youn Boo Steffen Allan Shelley D. Todd Griffith Alejandra S. Escalera Mendoza
Offshore floating wind foundations supporting a large wind turbine require a large yard facility or significant facility upgrades for their fabrication. To overcome the cost increase associated with facility upgrades, an innovative lightweight modular floating foundation is developed. The foundation comprises multiple modules to enable their assembly on water, offering many benefits and expanding fabrication options for a reduction in the overall cost of the platform. In this paper, the foundation modules and their assembly are briefly described, and an analysis of the platform’s dynamic responses is presented. The modular foundation includes a modular and lightweight tension leg platform (TLP) called “MarsVAWT” which supports a Darrieus 10 MW vertical axis wind turbine (VAWT). The platform is moored with highly pretensioned wire rope tendons. The responses of the platform are analyzed in the time domain in a semi-coupled manner under the turbine operating and parked conditions for an offshore site in the US Northeast. The tower base shear forces and bending moments increase considerably with the combination of wind and waves, compared to those with wind only. The tendon tensions on the weatherside in the operating condition at high wind speeds are comparable to the values of the 50-year extreme (parked). The tendon tension increases are highly correlated to the platform pitch, as well as the horizontal and vertical velocities and vertical acceleration at the tendon porch. The modular platform performances and tendon designs are confirmed to comply with industry standards and practices.
]]>Authors: Mirella Lima Saraiva Araujo Yasmin Kaore Lago Kitagawa Arthur Lúcide Cotta Weyll Francisco José Lopes de Lima Thalyta Soares dos Santos William Duarte Jacondino Allan Rodrigues Silva Márcio de Carvalho Filho Willian Ramires Pires Bezerra José Bione de Melo Filho Alex Álisson Bandeira Santos Diogo Nunes da Silva Ramos Davidson Martins Moreira
Wind power forecasting is pivotal in promoting a stable and sustainable grid operation by estimating future power outputs from past meteorological and turbine data. The inherent unpredictability in wind patterns poses substantial challenges in synchronizing supply with demand, with inaccuracies potentially destabilizing the grid and potentially causing energy shortages or excesses. This study develops a data-driven approach to forecast wind power from 30 min to 12 h ahead using historical wind power data collected by the Supervisory Control and Data Acquisition (SCADA) system from one wind turbine, the Enercon/E92 2350 kW model, installed at Casa Nova, Bahia, Brazil. Those data were measured from January 2020 to April 2021. Time orientation was embedded using sine/cosine or cyclic encoding, deriving 16 normalized features that encapsulate crucial daily and seasonal trends. The research explores two distinct strategies: error prediction and error correction, both employing a sequential model where initial forecasts via k-Nearest Neighbors (KNN) are rectified by the Extra Trees Regressor. Their primary divergence is the second model’s target variable. Evaluations revealed both strategies outperforming the standalone KNN, with error correction excelling in short-term predictions and error prediction showing potential for extended forecasts. This exploration underscores the imperative importance of methodology selection in wind power forecasting.
]]>Authors: Jan Euler Georg Jacobs Amin Loriemi Timm Jakobs Amadeus Rolink Julian Röder
Wind energy is an important renewable energy source. Rotor main bearings are critical components of wind turbines since a faulty main bearing leads to downtime and high repair costs. Operational expenditures amount to 32% of wind energy costs. The use of plain bearings as main bearings can potentially reduce these costs. Plain bearings with segmented sliding elements can be repaired up-tower without dismantling the drivetrain, as damaged segments can be exchanged individually. One such segmented plain bearing design is the conical plain bearing design called FlexPad. For the FlexPad, proof of concept was achieved for the 1 MW range during previous studies. Modern wind turbines—especially for offshore deployment—have increased in size significantly compared with their predecessors. The goal of current studies is to transfer the FlexPad design towards a main bearing unit at a market relevant scale of 8.5 MW. In this work, the identified scaling challenges are presented. A FlexPad model scaled to the 8.5 MW range is presented to illustrate the challenges. The bearing load components, such as radial forces and torque, increase on different scales with increasing rotor size leading to changed load characteristics with increasing size. Increased rotor weight and bearing diameters result in an increase in the breakaway torque required to start turbine rotation. This breakaway torque can exceed the torque generated by the turbine at starting wind speeds. The generally increased loads necessitate stiffer sliding segments leading to the increased weight of the segments, which hampers the ability to easily exchange segments.
]]>Authors: Lien Young Xing Zheng Erjie Gao
The global supply of energy is still tight, even with the rise of renewable energy utilization and abundant wind energy. More and more large wind farms have been installed globally. As of 2020, China’s total installed capacity accounted for 38.8%, far ahead of other countries. The layout of horizontal-axis wind turbine (HAWT) arrays in large wind farms poses three main issues: (1) How to select a site. (2) How to arrange the HAWT arrays to achieve greater power extraction at a specific wind farm. (3) How to reduce the noise generated by HAWTs. The numerical simulation of a HAWT wake field generally includes the analytical method (AM), vortex-lattice or vortex particle method (VM), panel method (PM), blade element momentum method (BEM), generalized actuator method (GAM), and direct modeling method (DM). Considering the computational cost, this paper combines DMs and mainly adopts the BEM-CFD coupling method, including uniform and non-uniform loading of axial force. Forty specially designed numerical experiments were carried out, which show that: (1) the BEM-CFD method greatly improves the calculation speed within the accuracy range of a thrust coefficient less than 2.5%, making it very suitable for the calculation of large wind farm HAWT arrays; (2) for regular HAWT arrays, it is reasonable to choose a 6D spacing in the wind direction and a 4D spacing in the crosswind direction for simplicity in practice.
]]>Authors: Zhen Pei He-Yong Xu Lei Deng Ling-Xiao Li
In this paper, the NWT600 airfoil with a thickness ratio of 60% is taken as the research object. The aerodynamic performance of the airfoil is analyzed by experiments and numerical simulations. The results simulated by various turbulence models used in the 2D steady-state RANS method are compared, including the Spalart–Allmaras model, k-ω SST model, k-ε realizable model, and Reynolds stress (linear pressure-strain) model. The influence of blunt trailing-edge thickness on aerodynamic characteristics is studied by adding thickness symmetrically. The results show that even under the low subsonic flow with a Mach number of 0.149, the airflow is prone to severe separation. The aerodynamic performance of the airfoil is very different from that of the conventional thin airfoil. Although the 2D steady-state RANS models overestimate the pressure on the surface of the airfoil in most cases, it is qualitatively acceptable to predict the pressure distribution of the very thick airfoil. Numerical results simulated by the Reynolds stress model are in the best agreement with the experimental data. It is also found that symmetrically thickening the trailing edge effectively improves the maximum lift coefficient and reduces the drag coefficient at a small angle of attack.
]]>Authors: Firoz Alam Yingai Jin
Liquid fossil fuel is anticipated to run out by the mid-2060s. The destruction of land, water, and air due to fossil fuel use contributes to environmental degradation. Policymakers, scientists, and researchers are looking into power generation from renewable sources, such as wind and solar energy, because of the threat of climate change owing to global warming brought on by greenhouse gas emissions. Although there have been substantial advancements in the use of large-scale wind turbines for power generation, small-scale wind turbines, which have the potential for solo power generation, have not received wider acceptance yet due to their lower-than-expected power generation performance. This study’s main goal is to analyse the limitations of harnessing wind energy by small-scale wind turbines for power generation in built-up areas for residential and commercial uses. The study focuses on the difficulties and potential of generating electric power from small wind turbines in urban settings. The state of wind characteristics in built-up areas, economic viability, aerodynamic limitations, and governmental regulations for small-scale wind turbines are also discussed.
]]>Authors: Wei Ding Yasushi Uematsu Lizhi Wen
The present paper investigates the fundamental characteristics of wind loading on vaulted (cylindrical) free roofs based on a wind tunnel experiment and a computational fluid dynamics (CFD) analysis using Large Eddy Simulation (LES). In the wind tunnel experiment, wind pressures at many points, both on the top and bottom surfaces of rigid roof models, were measured in a turbulent boundary layer. The wind tunnel models, including the tubing system installed in the roof and columns, were made using a 3D printer, which made the roof thickness as small as 2 mm, whereas the span B was 150 mm and the length L ranged from 150 to 450 mm. The rise-to-span ratio f/B ranged from 0.1 to 0.4. Pressure taps were installed along the center arc and an arc near the roof edge (verge) of an instrumented model with a length-to-span ratio of L/B = 1. The value of L/B of the tested models was changed from 1 to 3 using one or two dummy models, which had the same configuration as that of the instrumented model but no pressure taps. The wind direction θ was changed from 0° (perpendicular to the eaves) to ±90° (parallel to the eaves). The CFD simulation was carried out only for limited cases, that is, f/B = 0.1 and 0.4 and θ = 0° and 45°, considering the computational time. The effects of f/B, L/B, and θ on the mean (time-averaged) and fluctuating wind pressures acting on the roofs were investigated. In particular, the flow mechanism generating large wind forces on the roof was discussed. An empirical formula was provided for the distribution of mean wind force coefficients along the center arc (Line C) at θ = 0° and 30° and along the edge arc (Line E) at θ = 40° for each f/B ratio. Note that these wind directions provided the maximum and minimum mean wind force coefficients within all wind directions for Lines C and E. Furthermore, the maximum and minimum peak wind force coefficients on the two arcs were presented. The effect of turbulence intensity of approach flow on the maximum and minimum peak wind force coefficients was investigated. The experimental results were compared with those estimated using a peak factor approach, which showed a relatively good agreement between them. The data presented here can be used to guide the design of the main wind force-resisting systems and the cladding/components of vaulted-free roofs.
]]>Authors: Thays G. A. Duarte Srinivasan Arunachalam Arthriya Subgranon Seymour M. J. Spence
The simulation of stochastic wind loads is necessary for many applications in wind engineering. The proper-orthogonal-decomposition-(POD)-based spectral representation method is a popular approach used for this purpose, due to its computational efficiency. For general wind directions and building configurations, the data-informed POD-based stochastic model is an alternative that uses wind-tunnel-smoothed auto- and cross-spectral density as input, to calibrate the eigenvalues and eigenvectors of the target load process. Even though this method is straightforward and presents advantages, compared to using empirical target auto- and cross-spectral density, the limitations and errors associated with this model have not been investigated. To this end, an extensive experimental study on a rectangular building model considering multiple wind directions and configurations was conducted, to allow the quantification of uncertainty related to the use of short-duration wind tunnel records for calibration and validation of the data-informed POD-based stochastic model. The results demonstrate that the data-informed model can efficiently simulate stochastic wind loads with negligible model errors, while the errors associated with calibration to short-duration wind tunnel data can be important.
]]>Authors: Seyed Hassan Ashrafi Niaki Jalal Sahebkar Farkhani Zhe Chen Birgitte Bak-Jensen Shuju Hu
Large and remote offshore wind farms (OWFs) usually use voltage source converter (VSC) systems to transmit electrical power to the main network. Submarine high-voltage direct current (HVDC) cables are commonly used as transmission links. As they are liable to insulation breakdown, fault location in the HVDC cables is a major issue in these systems. Exact fault location can significantly reduce the high cost of submarine HVDC cable repair in multi-terminal networks. In this paper, a novel method is presented to find the exact location of the DC faults. The fault location is calculated using extraction of new features from voltage signals of cables’ sheaths and a trained artificial neural network (ANN). The results obtained from a simulation of a three-terminal HVDC system in power systems computer-aided design (PSCAD) environment show that the maximum percentage error of the proposed method is less than 1%.
]]>Authors: Lucas Touw Pablo Jaen Sola Erkan Oterkus
Rotor and stator support structures of significant size and mass are required to withstand the considerable loads that direct-drive wind turbine electrical generators face to maintain an air-gap clearance that is open and stable. With the increase of scale, reducing the weight and environmental impact of these support structures is believed to be one of the key components to unlocking the true potential of direct-drive generators. An investigation on the electrical generator rotor structure of the IEA 15 MW offshore reference wind turbine was conducted. An integrated approach that considered the environmental impact, including the manufacturing energy usage and CO2 footprint, as well as the financial repercussions of structural parameter modifications as they are optimised was followed, making use of distinct commercial pieces of software. The rotor structure was parametrically optimised, and its operating loading conditions were evaluated at various size scales. The study determined that the effect of thermal loading is significant, which forces the designer to augment the mass to comply with the imposed structural requirements. The ensuing life-cycle assessment showed an increase in the environmental impact due to the consideration of this particular load, whose effect in structural deflection and stress has been typically underestimated.
]]>Authors: Vahid Akbari Mohammad Naghashzadegan Ramin Kouhikamali Wahiba Yaïci
This research investigates the effect of blade density and elevation above sea level on the startup time (Ts) and power coefficient (Cp) of a 1-kW two-bladed wind turbine. The study uses three Iranian hardwoods as the blade material and four counties of Iran with low wind speeds and different elevations as the case studies. The BW-3 airfoil is considered as the blade profile. A multi-objective optimization process with the aid of the differential evolution (DE) algorithm is utilized to specify the chord length and twist angle. The findings demonstrate that, while the maximum Cp of the optimal blades designed with all three types of wood is high and equal to 0.48, the average Ts of the optimal blades designed with oak and hornbeam wood is 84% and 108% higher than that of alder wood, respectively. It is also observed that, while raising the elevation to 2250 m decreases the Cp by only 2.5%, the ideal blade designed to work at sea level could not manage to start rotating at a height of 1607 m and above. Finally, an improvement in the Ts and Cp was observed by performing optimization based on the local atmospheric conditions associated with the incrementing blade chord length at high elevations.
]]>Authors: Anica Frehn Jens Sdun Rayk Grune Antonello Monti
In recent years, nacelle test benches for wind turbines have been developed internationally. New standards are currently being developed that explicitly refer to the measurement of the electrical properties of wind turbines on these test benches. Thus, they are suitable for measuring the electrical properties required for certification. Another part of the certification is the creation and validation of suitable models of the wind turbine, which are used for stability analyses of the utility grid. Validation requires a suitable model of grid replication on the test benches, which is not yet covered by any applicable standard. Such models should be as simplified a representation of the artificial grid replication as possible to ensure that they are accessible to certification bodies. A model of the grid emulator installed at the CWD of RWTH Aachen University, which was validated with real measurement data, serves as a reference. A step-by-step reduction of the model’s depth up to the system’s technical representation is followed by a model evaluation with respect to the level of detail and an analysis of time and frequency. The evaluation shows that even a highly simplified model consisting of a reference voltage and an impedance replica meets the requirements for the validation of wind turbine models according to IEC 61400-27-2.
]]>Authors: Bethany G. Thurber Ryan J. Kilpatrick Graeme H. Tang Christa Wakim J. Ryan Zimmerling
Wind energy is a growing industry in Canada to meet the demand for a renewable supply of energy. However, wind turbine operation represents a high mortality risk for bat populations, and regulators often require that steps are taken to mitigate this risk. The result is concern among operators about lost revenue potential. This study was, therefore, designed to estimate the theoretical financial impact of curtailing turbine operations to mitigate for bat mortality for all wind farms that were constructed and operating in Ontario, Canada, as of 1 January 2020 (n = 87 wind farms). Empirical data from the Canadian Wind Farm SCADA and meteorological systems are not publicly available; thus, we were compelled to use data from the Canadian Wind Turbine database, the Environment and Climate Change Canada Wind Atlas, and the Independent Electricity System Operator to calculate the total theoretical energy production for all wind turbines in the province using manufacturer power curves and a measure–correlate–predict linear regression method. We estimated the financial impacts for all wind farms on the assumption that operations were curtailed when the Wind Atlas modelled local wind speed was <5.5 m/s between 6 pm of one day and 6 am the following day, between 15 July and 30 September, using the lower and upper limits of power-purchase agreement rates for Ontario wind farms: 115 and 150 CAD/MWh. We used generalized linear modelling to test whether the variability in production loss was predicted based on factors related to turbine design and site wind speeds. We estimated that total annual wind energy production would be reduced from 12.09 to 12.04 TWh if all Ontario wind farms implemented operational curtailment, which is equivalent to a difference of 51.2 GWh, or 0.42%. Production loss was related to turbine cut-in speeds and average site wind speeds recorded between 15 July and 30 September. The estimated profit losses were 6.79 ± 0.9 million CAD compared to estimated earnings of 1.6 ± 0.21 billion CAD, which suggests that mitigating bat mortality may represent a small cost to the industry relative to the conservation benefits for bat populations.
]]>Authors: Denes Fischer Benjamin Church Christian Navid Nayeri Christian Oliver Paschereit
The potential of airfoil optimisation for the specific requirements of airborne wind energy (AWE) systems is investigated. Experimental and numerical investigations were conducted at high Reynolds numbers for the S1223 airfoil and an optimised airfoil with thin slat. The optimised geometry was generated using the NSGA-II optimisation algorithm in conjunction with 2D-RANS simulations. The results showed that simultaneous optimisation of the slat and airfoil is the most promising approach. Furthermore, the choice of turbulence model was found to be crucial, requiring appropriate transition modeling to reproduce experimental data. The k-ω-SST-γ-Reθ model proved to be most suitable for the geometries investigated. Wind tunnel experiments were conducted with high aspect ratio model airfoils, using a novel structural design, relying mostly on 3D-printed airfoil segments. The optimised airfoil and slat geometry showed significantly improved maximum lift and a shift of the maximum power factor to higher angles of attack, indicating good potential for use in AWE systems, especially at higher Reynolds numbers. The combined numerical and experimental approach proved to be very successful and the overall process a promising starting point for future optimisation and investigation of airfoils for AWE systems.
]]>Authors: Jielong Cai Sidaard Gunasekaran
The RC propeller performance under steady and sinusoidally time-varying freestream (stream-wise or longitudinal gust) was investigated in the University of Dayton Low-Speed Wind Tunnel (UD-LSWT) in the open-jet configuration. The propellers were tested at varying incidence angles and reduced frequencies. The streamwise gust was created by actuating the shuttering system located at the test section exit and was characterized using hot-wire anemometry. A system identification model was developed for the shuttering system to determine the shutter actuation profile that would result in a sinusoidal gust in the test section. Changes in propeller thrust, power, and pitching moment were observed with an increase in propeller incidence angle under the steady freestream. The propeller’s steady freestream performance was then used to predict response under periodic streamwise gusts in edgewise flight. Below a reduced frequency of 0.2, the propeller response agrees with the prediction model, suggesting that the propeller response is quasi-steady. At reduced frequencies higher than 0.2, a reduction in mean thrust and pitching moment and significant phase lag was observed.
]]>Authors: Samuel dos Santos Bettoni Herbert de Oliveira Ramos Frederico F. Matos Victor Flores Mendes
With the growing expansion of renewable sources around the world, wind energy is among those that stand out. With the advances of technology, wind turbine projects have considerably increased their power, reaching higher power, mainly for offshore installations. One of the main challenges is the power converters, more specifically the semiconductor components, which have limited voltage and current capabilities. Thus, the concept of multilevel converters emerged, increasing the voltage levels and thus carrying higher power levels. In addition to the application of multilevel converters, it is possible to increase the voltage and power levels employing an open-end winding (OEW) connection to the generator. In this context, the present work investigated the application of a multilevel converter (three-level cascaded H-bridge back-to-back) driving a squirrel-cage induction machine in an open-end winding configuration, connected to a wind energy conversion system (WECS). The analysis of the proposed system was developed through dynamic simulation of a 1.67 MW WECS, using PLECS software, including the modeling of the main system components: generator, power converters, system control, filter, and grid connection. The results show that the objective of obtaining a 5-level behavior in the output voltage is achieved by using the OEW connection. Furthermore, a low harmonic content is achieved in the machine current as in the current injected into the grid. In addition, it is possible to verify the power distribution between the converters, demonstrating that converters with smaller power can be combined to reach higher WECS power.
]]>Authors: Abubaker Younis Hazim Elshiekh Duaa Osama Gamar Shaikh-Eldeen Amin Elamir Yassir Yassin Ali Omer Elfadil Biraima
In this quick study, we estimated the Weibull distribution’s parameters using wind data collected between March 2017 and January 2018 using a twelve-meter mast meteorological station on the grounds of the National Energy Research Center in Khartoum. In order to quantify these descriptors, we relied on analytical and stochastic methods, subsequently enabling specialists from researchers, engineers, decision-makers, and policymakers to apprehend the wind characteristics in the vicinity. Hence, the computed scale and shape parameters were provided, in which the Firefly algorithm (FA) resulted in the most accuracy in terms of the coefficient of determination, which equaled 0.999, which we considered logical due to the observed nonlinearity in the wind speed numbers. On the contrary, the energy pattern factor method had the worst prediction capability depending on several goodness-of-fit metrics. This concise work is unique because it is the first to use data from Sudan to forecast local wind speeds using artificial intelligence algorithms, particularly the FA technique, which is widely used in solar photovoltaic modeling. Additionally, since classic estimating approaches act differently spatially, evaluating their efficacy becomes innovative, which was accomplished here. On a similar note, a weighted-average wind speed was found to equal 4.98 m/s and the FA average wind speed was 3.73 m/s, while the rose diagram indicated that most winds with potential energy equivalent to 3 m/s or more blow from the north.
]]>Authors: Qiqing Zhang Xiuling Wang
As one of the preferred types of renewable energy, wind energy is rapidly growing. The purpose of this study is to provide a comprehensive and in-depth numerical analysis on the National Renewable Energy Lab (NREL) 5-MW offshore wind turbine to help understand the wind turbine’s aerodynamic features. In this research, the preprocessing was conducted by using SolidWorks modeling, and a realizable k-ε viscous model from ANSYS/FLUENT was used as the solver in the CFD simulation. Eight test cases were developed, and fixed inlet velocity 9 m/s was set as the baseline case. After the initial mesh independent study and model validation, a detailed numerical analysis was carried out. The results of near wake flow features, torque and thrust, pressure and pressure coefficient distribution, limiting streamline along wind turbine blades, power coefficient as a function of tip speed ratio were evaluated. Whenever possible, simulation results were compared with data in the literature (numerical or experimental), and good agreement was observed. The detailed wind turbine aerodynamic analysis results are expected to provide valuable input to wind turbine design and thus to improve the effectiveness of harnessing wind energy. Research is on the way to further understanding the influence of different inflow conditions on the aerodynamic characteristics.
]]>Authors: Marieli Azoia Lukiantchuki Alessandra Rodrigues Prata Shimomura Fernando Marques da Silva Rosana Maria Caram
Most of the Brazilian territory is classified as a hot and humid climate, whose natural ventilation is one of the most important passive design strategies. The use of this strategy can be enhanced in the design through the shed roof air collectors or extractors. However, this strategy is not exploited by architecture design, due to the designers’ lack of knowledge about the efficiency of these devices. The article’s aim is to present guidelines for the design of shed roof air extractors and collectors, seeking to help designers to use these devices in buildings. The method is parametric studies, through CFD simulations. For the shed roof air extractors and collectors, the following is recommended: aerodynamic geometries; building with less depth and large air outlet openings. The increase in the number of sheds influences ventilation more than the change in the geometry of the sheds. For extraction, the area of the air outlet openings is the parameter that exerts the greatest influence on ventilation. For collection, the increase in the sizes of the openings of the sheds, without changing other parameters, does not significantly increase the air speed.
]]>Authors: Damjan Bujak Tonko Bogovac Dalibor Carević Hanna Miličević
Wave data play a critical role in offshore structure design and coastal vulnerability studies. For various reasons, such as equipment malfunctions, wave data are often incomplete. Despite the interest in completing the data, few studies have considered constructing a machine learning model with publicly available wind measurements as input, while wind data from reanalysis models are commonly used. In this work, ANNs are constructed and tested to fill in missing wave data and extend the original wave measurements in a basin with limited fetch where wind waves dominate. Input features for the ANN are obtained from the publicly available Integrated Surface Database (ISD) maintained by NOAA. The accuracy of the ANNs is also compared to a state-of-the-art reanalysis wave model, MEDSEA, maintained at Copernicus Marine Service. The results of this study show that ANNs can accurately fill in missing wave data and also extend beyond the measurement period, using the wind velocity magnitude and wind direction from nearby weather stations. The MEDSEA reanalysis data showed greater scatter compared to the reconstructed significant wave heights from ANN. Specifically, MEDSEA showed a 22% higher HH index for expanding wave data and a 33% higher HH index for filling in missing wave data points.
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