Search Results (117)

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

The estimation of the aerodynamic characteristics of a rough surface (zero displacement plane $d_0$ and aerodynamic roughness length $z_0$) 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 $d_0$ and $z_0$ 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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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 $H/B_0$ (=2, 4, and 8), where $B_0$ (=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. Full article

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. Full article

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. Full article

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 $R^2$ 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. Full article

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. Full article