Wind

This study presents an integrated framework for offshore wind resource assessment and wind farm micrositing in the Northern Aegean Sea of Türkiye by combining machine learning-assisted measure–correlate–predict (MCP) modelling, long-term reanalysis data and computational fluid dynamics (CFD). One year of measurements from a 41 m meteorological mast on Küçük Ada, offshore Aliağa, İzmir, was analyzed together with a 21-year ECMWF Reanalysis v5 (ERA5) dataset. The measurements indicated a mean annual wind speed of 8.07 m/s, a wind shear exponent of 0.049, a Weibull shape parameter of 2.06 and a persistent northeasterly wind regime. Long-term conditions were reconstructed using 64 meteorological and cyclic predictors derived from four ERA5 grid points and their bilinear interpolation to the mast location. Five H₂O algorithm families were evaluated using randomized grid searches and 12-fold temporal cross-validation. Distributed Random Forest provided the best performance for 100 m wind speed, with RMSE = 1.969 m/s, MAE = 1.504 m/s, bias = −0.027 m/s and an out-of-fold Pearson correlation coefficient of r = 0.884. TreeSHAP analysis was applied to interpret predictor contributions. High-resolution WindSim simulations with 28.75 million cells, ALOS PALSAR topography and CORINE land-cover data supported turbine micrositing. The proposed 1.43 GW wind farm yielded 5494.5 GWh/year after wake losses, with a capacity factor of 43.9% and an overall wake loss of 5.2%. The framework provides a robust basis for offshore wind development in Türkiye. Full article

Vertical-axis wind turbines (VAWTs) could be a good alternative to horizontal axis turbines for offshore applications. However, the variability of the aerodynamic forces with the blade azimuthal position subjects the blade to fatigue stresses and generates typical power periodicity. Extreme wind conditions, such as gusts, could aggravate the aerodynamic load peaks, compromising the system durability. We analyze the transient aerodynamic loads generated under gusty winds for a 5 MW offshore troposkein-shaped VAWT. The behavior of the turbine at its equatorial plane is simulated by 2D-CFD assuming gusts characterized by different periods and amplitudes. Since the turbine is stall-regulated, a range of wind velocities going from the maximum efficiency velocity to the nominal power velocity are considered. The instantaneous overloads of power, blade radial force, and total force on the shaft are analyzed. An increase in the peak values up to 119% (power) and 51% (force on the shaft) are predicted relative to the most severe steady condition, depending on gust characteristics and the blade position when the gust crest occurs. These results refer to the equatorial plane, rather than the entire turbine. It is demonstrated how the passive stall load regulation method protects the turbine from excessive overloads. Full article

Conventional vertical-axis wind turbines (VAWTs) rely on rigid blades that are heavy and require expensive materials and manufacturing processes to withstand aerodynamic loads. This study explores flexible sail-type blades as a low-cost alternative capable of achieving comparable performance. Small-scale sail-type VAWTs employing blades made out of fabric similar to maritime sails were designed, fabricated, and tested in a wind tunnel. One edge of each sail was hemmed to a vertical rod, while the opposite edge was secured at its end to top and bottom end disks. The turbine radius and height were fixed at 19 cm and 21 cm, respectively. Experiments were conducted in a wind tunnel and measurements included wind speed, turbine rotational speed, and the generator current and voltage. A total of 36 configurations were evaluated by varying four design parameters: number of sails (2, 3, and 6), chord length (10 cm and 15 cm), pitch angle (0°, 15°, 30°, and 45°), and blade shape (rectangular or trapezoidal). Performance was assessed using power output (P), power coefficient (Cp), and tip-speed ratio (TSR). Experimental results were validated by comparison with test data for a conventional rigid-bladed VAWT. The best-performing configuration was a three-sail turbine with rectangular blades, 15 cm chord length, and 0° pitch angle, producing 547 mW at 177 RPM, corresponding to a Cp of 0.053 at a TSR of 0.59. Numerical predictions using state-of-the-art codes were used to further assess sail-type VAWT performance. Under the test conditions considered, the sail-type VAWT not only showed better performance but also comparable self-starting capability compared to a rigid-bladed VAWT. However, due to the maximum wind speed limitation of the test facility, the complete Cp-TSR characteristic curve could not be determined. Moreover, preliminary estimates indicate a potential 24% reduction in total turbine capital cost and an overall 30% reduction in turbine mass of sail-type turbines over conventional HAWTs, demonstrating that flexible sail blades are a promising low-cost option that needs further investigation to realize their full potential. Full article

As de-icing and anti-icing blade heating systems for wind turbines continue to mature, operators have developed a clearer understanding of both their benefits and their limitations. This growing operational experience has increased the need for warranty frameworks that can verify whether such systems perform as intended under real icing conditions. This study builds upon existing approaches to blade heating system warranties and, based on case studies, proposes practical methods to improve them. The principal challenge lies in separating meteorological risk, namely the frequency and severity of icing events, from technological risk, namely the availability and effectiveness of the blade heating system. This paper provides an extensive review of existing approaches to blade heating system warranties and proposes a practical self-comparison methodology for evaluating turbine-level performance using measured operational data. The method defines the applicable warranty period from external icing measurements, excludes periods of active meteorological icing to reduce the influence of site-specific exposure, and evaluates the remaining production shortfall using the Warranted Icing Compensable Energy, WICE. The methodology is applied to five case studies from four wind farms, four turbine manufacturers, and four blade heating technologies. The proposed framework provides a transparent and operationally applicable bridge between existing warranty guidelines and the detailed implementation rules required for commercially meaningful performance assessment of wind turbine blade heating systems. Full article

This study evaluates the effects of sampling interval and averaging period on the assessment of extreme synoptic-scale mean wind speeds for structural design, excluding hurricanes and mesoscale events, to focus on correction factors for the standard meteorological observations that are archived for more than 35,000 stations around the globe. A literature review reveals insights and flaws in past works that influenced the design of the two phases of the study. The first phase uses 2-minute mean wind speeds at 1 min intervals over, typically, 20 years from 642 well-exposed stations distributed over the contiguous USA that are averaged to the World Meteorological Organization standard ten-minute and hourly means. Informed by the first stage results, which confirm good representation by the Weibull distribution with a von Karman autocorrelation, the second phase uses simulated 1000-year time series to investigate the parameters governing the effects, which are: sampling interval, averaging period, integral timescale of the autocorrelation, and the return period of the extremes. The effects of these four parameters, in any combination, consolidate into a single analytical equation with empirically calibrated coefficients, which is a good match to the empirical analysis of the first phase, when using the appropriate integral timescale. Full article

This study evaluates the offshore wind resource along the Mauritanian Atlantic coast, focusing on ten offshore zones and hub heights up to 100 m. The primary objective is to characterize the spatial variability of the wind resource and provide a preliminary assessment of offshore energy potential. Wind speed data derived from ERA5 were analyzed using Weibull distribution parameters, wind power density, and turbine-based energy production estimates. To support the preliminary identification of suitable offshore wind sites, the study also considers bathymetric conditions, marine spatial constraints, preliminary geotechnical aspects, and uncertainty analysis. The results reveal a systematic increase in wind speed with height and a pronounced north–south gradient along the coast. Zone 1 (Nouadhibou) exhibits an annual mean wind power density of 740.84 W/m², with a monthly maximum of 1237.27 W/m² observed in June, confirming the exceptional wind conditions in the northern offshore zones. The bathymetric analysis indicates that the northern and central sectors are generally more suitable for fixed-bottom foundations, whereas deeper offshore areas may require floating wind technologies. Although these findings provide a robust preliminary assessment of the offshore wind potential, further geophysical and geotechnical investigations, together with environmental and techno-economic assessments, are required before confirming the suitability of the identified sites. Overall, this work provides a first technical framework for the preliminary identification and comparison of promising offshore wind zones along the Mauritanian Atlantic coast. Full article

Flux-modulating machines are emerging as noteworthy machines, particularly in wind turbines. Due to their brushless medium-speed operations, they can be deployed for applications where reliability is a critical factor. Two popular machines in this category are brushless doubly fed machines (BDFMs) and wound-field flux-switching machines (WFFSMs). Although these machines work according to similar flux cross-coupling principles, they have almost contrasting descriptions. While the low power density (power per volume) of BDFMs is well documented in the literature, WFFSMs are commonly touted for their high power densities. In this paper, the performances of BDFMs and WFFSMs are compared to harmonize the perspective on their performances in wind generation applications. It is revealed that the compared BDFM and WFFSM topologies have identical performances with some notable nuances. They generate similar power for a given volume, with the WFFSM having greater efficiency, but they have lower power factors. Compared with conventional topologies like doubly fed induction generators, both flux-modulating topologies have considerably lower power densities. Nevertheless, it has been demonstrated that some design insights for one topology (WFFSM or BDFM) are transferable to the other, such as high-performing pole-pair combinations and magnetic loadings. It should also be noted that design developments such as dual stator configurations are beneficial for both topologies, as they enable significant increases in the power generated for a given volume. Full article

Wind turbine blade defect detection in complex environments is challenged by weak defect features, missed crack detections, and false detections caused by background interference. To address these problems, this study proposes an improved YOLOv8n-based detection model. First, MS-CBAM is introduced before the SPPF module to enhance channel-wise feature refinement and multi-scale spatial feature extraction. Second, four stride-2 downsampling convolutional layers in the backbone are replaced with EPConv, which combines efficient multi-scale channel attention with directional pinwheel-shaped convolution to strengthen the representation of weak and elongated defects. Finally, the original CIoU loss is replaced with PIoU v2 to improve bounding-box regression. Experiments on a self-constructed wind turbine blade defect dataset show that the proposed model achieves a precision of 92.1%, a recall of 85.1%, an mAP_0.5 of 90.7%, and an mAP_0.5:0.95 of 68.0%. Compared with the original YOLOv8n, these values represent improvements of 0.4, 5.9, 3.9, and 5.2 percentage points, respectively. The model contains approximately 3.0 M parameters, requires 8.9 GFLOPs, and achieves a network-forward inference speed of 77.1 FPS on an NVIDIA GeForce RTX 5060 Laptop GPU. Class-wise evaluation further shows that crack AP_0.5 increases from 78.4% to 85.0%, while crack AP_0.5:0.95 increases from 50.7% to 55.9%. These results demonstrate that the proposed modifications improve the detection and localization of weak and elongated defects while maintaining real-time inference capability on the tested GPU platform. Full article

Boundary-layer atmospheric stability, wind-shear variability, and thermodynamic forcing are all important factors for the initiation, intensification, and transport of dust storms. But there is limited knowledge of the quantitative evaluation of bulk-layer atmospheric stability and the relation between wind-driven dust dynamics and atmospheric stability in arid and semi-arid regions. In this research, a hybrid AI–meteorology framework, HyMet-Fusion, is presented that combines visual information derived from satellite observations with physics-based indicators of atmospheric stability to evaluate atmospheric stability during dust storm events over Iraq. The proposed framework is based on the use of deep features extracted from the satellite imagery through a frozen EfficientNetB0 backbone, combined with indicators derived from the ERA5 pressure level data for the atmosphere, such as the Bulk Richardson Number (Bulk Ri), the Wind Shear (WS) and the Dry Air Index (DAI). The two branches were merged using a late fusion (0.75 physics/0.25 image) and each hour was classified into three atmospheric stability conditions: Relatively Stable, Moderately Unstable and Unstable. The overall hourly accuracy using a Leave-One-Event-Out (LOEO) cross-validation scheme, where each dust event was used for independent testing and no dust event was used for training, was 72.4%, with 81.2% accuracy for the dominant stability state and 92.2% correct assessment of the unstable condition time for the severe dust events. Inaccuracies were mainly (66%) in the conservative direction (more instability). Unstable atmospheric conditions were also found to be associated with all severe dust storms and coincided with higher wind shear, lower Bulk Ri values and higher thermodynamic variability. Moderate and light dust events were primarily associated with transitional and relatively stable atmospheric conditions, and differed between the various regions, primarily in Kirkuk and Nasiriyah. Correlation analysis showed that wind shear had the highest correlation with atmospheric instability (r = 0.92), followed by DAI (r = 0.90) and Bulk Ri (r = −0.75). In addition, the wind shear also increased significantly from light to severe dust events at all stations investigated, showing that wind shear is a critical factor for turbulent mixing, vertical momentum exchange and dust uplift processes. The results suggest wind shear is the leading dynamics mechanism for bulk-layer instability in Iraqi dust storms. The findings highlight the complementary benefit of using physics-based atmospheric indicators embedded with deep learning satellite image analysis. The HyMet-Fusion system can be used as a transferable method for observing wind-driven instability of the atmosphere and related dust hazards, which could be employed in boundary-layer meteorology, air-quality forecasting, aviation safety and environmental risk assessment in arid and semi-arid areas. Full article

The increasing global demand for clean energy has established wind power as a leading solution for sustainable electricity generation. The efficiency and reliability of wind turbines are strongly influenced by blade design, which governs both aerodynamic performance and structural integrity. In this study, a wind turbine blade based on the National Advisory Committee for Aeronautics (NACA) 4412 airfoil was developed for composite manufacturing, with variations in laminate layers (4, 8, 12, and 16) to optimize stiffness, strength, and weight. To reduce prototyping costs and development time, the structural response under operational loads was simulated using ANSYS Workbench 2025 R1. The Taguchi method was employed to minimize the number of experimental trials, considering three factors at four levels each. A multi-objective optimization was then performed to minimize tip deformation and maximum stress while ensuring a safe failure index. The results indicated that force distance was the most influential factor, followed by laminate configuration, while force magnitude had a comparatively smaller effect within the tested range. The configuration with a force of 15 N, a force distance of 60 cm, and 12 laminate layers achieved a composite desirability of 0.9413, leading to a significant reduction in deformation and stress while maintaining structural safety. These findings validate the effectiveness of the proposed design and optimization framework and provide practical guidelines for the development of high-performance composite wind turbine blades. Full article

This study investigates how offshore wind farm layout geometry influences farm-level performance using a computationally efficient Jensen–Park wake model combined with directionally resolved Weibull wind-speed statistics. A fixed-capacity 1.8 GW case study, consisting of 120 V236-15.0 MW turbines, is used to examine the effects of grid aspect ratio, inter-turbine spacing, cumulative row skew, and global layout rotation on wake losses, annual energy production (AEP), and capacity factor under representative offshore screening assumptions. Structured layouts with identical turbine count and installed capacity are compared with a regular baseline grid to isolate geometric effects within a consistent modelling framework. For the nominal offshore Jensen wake-expansion coefficient, k = 0.04, the highest sampled AEP is obtained for the 5 × 24 configuration, which produces 8930.69 GWh yr⁻¹ and a capacity factor of 56.64%. The regular baseline produces 7397.50 GWh yr⁻¹ and a capacity factor of 46.91%, corresponding to a 20.73% AEP increase for the highest sampled layout. However, the performance differences among Layouts D–F are small, indicating a high-performing layout plateau rather than a clearly separated optimum. The contribution of this paper is therefore not a new wake model, optimisation algorithm, or general offshore design rule. Instead, this study provides an auditable screening workflow that documents modelling assumptions, parameter bounds, coordinate transformations, convergence checks, sensitivity analyses, and spatial-efficiency indicators for one turbine model, one turbine count, one synthetic wind rose, and a limited set of structured row–column layouts. Full article

Extreme wind speed events pose a significant threat to structural safety and are an important consideration in the design of the growing renewable energy sectors. This study models extreme wind speeds in Namibia by applying Extreme Value Theory (EVT) to quality-controlled daily maximum wind speed records from six meteorological stations, spanning 13–21 years per station and covering the 2003–2024 period. A two-rule quality-control procedure, combining a regional plausibility limit with an isolated-spike test supported by cross-station coherence checks, identified and removed 70 spurious automatic weather station records (0.24% of observations) prior to analysis. The Generalized Pareto Distribution (GDP) was fitted to declustered threshold exceedances using the Peaks-Over-Threshold method, with 95% confidence intervals for return levels obtained by profile likelihood. Model comparison based on AIC, BIC, and the negative log-likelihood indicated that the Generalized Pareto Distribution (GPD) provided a better description of the extreme wind speed tails. The results reveal a clear coastal-inland contrast; the coastal station Lüderitz experiences the strongest and most frequent extreme wind events, with a 100-year return level of 49.4 m/s (GPD; 95% profile-likelihood interval 44.9–70.3 m/s) and evidence of a bounded upper tail, while inland stations exhibit more moderate extremes with 100-year return levels 36–45 m/s. A seasonal analysis reveals stronger winter extremes at coastal Walvis Bay, while inland stations experience summer convective peaks. The study provides the first systematic station-level EVT analysis of observed wind extremes for Namibia, offering essential quantitative input for wind-sensitive infrastructure design, renewable energy project siting, and national climate adaptation planning. Full article

The doubly fed induction generator (DFIG) dominates the wind energy market, yet its direct stator-to-grid connection makes it vulnerable to grid faults, creating a tension between hardware self-protection and grid-code fault ride-through (FRT) compliance. This paper presents the modelling and FRT analysis of a 9 MW DFIG wind farm combining a 20 MVA Static Synchronous Compensator (STATCOM) with a ten-tier algorithmic protection scheme. A detailed phasor-domain MATLAB/Simulink R2024b model is complemented by physics-based reduced-order models integrated in Python, separating calibration targets, calibration-dependent derived quantities and quantities independent of the DC-link calibration. The aerodynamic model reproduces the power coefficient maximum of 0.48 at a tip–speed ratio of 8.1. The energy-balance model uses two parameters identified per scenario from the detailed DC-link trajectory; its peak-voltage agreement within 0.4% is therefore a calibrated consistency check, while the derived arming times, slopes, chopper sizing and latency budget remain conditional on that calibration. A first-order Thevenin analysis shows that the STATCOM supports a weak 25 kV point of common coupling of order 53 MVA short-circuit level, not the 2500 MVA source. The approximate 0.50-to-0.78 p.u. recovery requires about 29.7 M_var and 1.90 p.u. of STATCOM rated current for 150 ms, conditional on an assumed short-time envelope and adequate converter-voltage headroom; it is not attributable to continuous rated operation. FRT support for the selected recoverable dip is separated from converter survival during a zero-impedance fault, for which a 1700 V chopper pickup with a 1 ms gate delay, not the 10 ms isolation command, is the clamping mechanism. The assessment is explicitly conditional and requires electromagnetic-transient and hardware-in-the-loop confirmation. Full article

Accurate modeling of wind turbine power curves is essential for performance assessment, energy forecasting, condition monitoring, and operational optimization in wind energy systems. This study presents a SCADA-based comparative assessment of established power curve modeling approaches through a single-site case study conducted on a low-power Vertical Axis Wind Turbine (VAWT) operating under real environmental conditions at the University of the Isthmus, located in the Isthmus of Tehuantepec, Oaxaca, Mexico. The evaluated methods included the maximum power curve, an aerodynamic model based on Blade Element Momentum Theory (BEMT), parametric approaches using polynomial and logistic regressions, and non-parametric data-driven methods based on Random Forest (RF), Gaussian Process Regression (GPR), and Kernel Density Estimation (KDE). One year of SCADA data, including wind speed and generated power measurements, was analyzed, while model performance was assessed using RMSE, MAE, and R² metrics. The results showed that the machine learning approaches achieved the lowest prediction errors among the evaluated models, with RF providing the best overall performance (RMSE = 7.4%, MAE = 4.8%, R² = 0.9814), followed by GPR and KDE under the investigated operating conditions. Additionally, Weibull analysis yielded parameters of k = 1.887 and c = 7.875 m/s, while the largest prediction errors were observed within the partial-load operating region (approximately 4–10 m/s) and as the turbine approached the rated operating condition (approximately 10–12 m/s). These findings indicate that, for the investigated low-power VAWT operating at the experimental site, non-parametric approaches provided the most accurate representation of the power curve among the evaluated models, highlighting the potential of SCADA-based data-driven techniques for comparative model assessment under similar operating conditions. Full article

Understanding wind direction (WD) variability and vertical directional shear is critical for aviation safety, particularly during landing when aircraft are highly sensitive to abrupt wind changes. This study analyzes the temporal behavior of WD and low-level directional shear over Baghdad International Airport during representative months of 2024 (January, April, July, and October) using hourly ERA5 u and v wind components at 10 and 540 m. Circular statistical measures quantify WD variability, while directional shear roses and absolute directional shear change rates characterize vertical wind alignment and shear intensity relevant to aviation operations. The results reveal pronounced seasonal contrasts. Summer (July) shows the most stable wind regime with strong directional persistence and weak shear (<~0.1–0.15 °/m), winter (January) is generally stable but punctuated by synoptic shear peaks up to ~0.85 °/m, spring (April) exhibits moderate and more variable shear (~0.1–0.45 °/m), and autumn (October) is the most dynamically unstable, with reduced persistence and frequent shear maxima approaching ~0.9–0.95 °/m. Circular standard deviation (σ_dir), is highest in winter–spring (mea n≈ 38° in January and ≈34° in April), weakest in summer (≈16–17° in July), and increases again in autumn (≈28–33° in October), reflecting seasonal changes in atmospheric forcing. σ_dir exhibits a clear seasonal cycle, with highest values during winter and spring and the most stable conditions in summer. These results show that integrating ERA5-based circular wind statistics with directional shear diagnostics effectively identifies aviation-critical wind regimes, while future multi-year and aircraft-based analyses can further refine operational low-level wind shear risk thresholds. Full article

High-sided vehicle safety on exposed long-span bridges depends on local wind direction as well as wind speed. Using a previously validated full-scale computational fluid dynamics model of the Queensferry Crossing Bridge, this study presents a two-stage site-specific assessment for double-decker buses. First, 50-year return period hourly means and one-second gust wind conditions from twelve directions are used to screen for the most adverse aerodynamic response. Within the present modelling framework, directions of 210°, 240°, 270° and 300° produce the largest changes in side force, lift force and rolling moment and are selected for further analysis. Second, a threshold-based operational assessment is carried out for these directions using the existing 60 mph gust closure threshold for double-decker buses and a moving-bus URANS (Unsteady Reynolds-Averaged Navier–Stokes) model. Safety factors for sideslip and overturning are evaluated to assess whether direction-dependent local wind effects create different levels of vulnerability under the same threshold. Additional simulations varying gust speed and bus speed examine the trade-off between local wind effects and vehicle speed in the most adverse direction. The framework links directional screening with operational safety assessment and shows that the same 60 mph gust threshold can correspond to materially different risk levels and mechanisms depending on wind direction. Full article

In order to reduce aviation’s negative environmental effects and support international efforts to battle climate change, the International Civil Aviation Organization (ICAO) seeks to cut greenhouse gas (GHG) emissions. About 2–3% of the world’s CO₂ emissions come from aviation, and at high altitudes, the fraction of other GHGs that significantly alter the atmosphere is considerably greater. In this study, hourly wind speed data at 100 m height from ECMWF’s fifth-generation reanalysis (ERA-5) were used over a period of 40 years (1985–2025). Hourly assessments of wind speeds at 40 m and 80 m heights are conducted in ERA-5, with biases at specific ground locations rectified via the Global Wind Atlas (GWA). This research estimates and analyzes many factors, including Weibull statistical parameters, daily and monthly wind speed variations, cumulative distribution function (CDF), and atmospheric turbulence intensity. The energy generation from several wind turbine types at different elevations was assessed. The findings indicate that the examined location revealed fair potential for the construction of large-capacity wind energy units at heights equal to or above 80 m. Turbines that are less than 50 m tall are spread out at least 10 km around the airport runway. While turbines that are less than 150 m tall are spread out at least 15 km away from the airport runway. Full article

The success of wind energy projects depends on reliable site selection and cost-effective operation. Existing studies largely focus on either resource potential or standalone economic feasibility, while a unified wind power rating framework for site prioritization across India remains lacking. This study proposes a multi-criteria wind power assessment framework and investigates the spatial and scale-dependent variability of wind speed (WS) and wind power density (WPD) over six major regions of India. Hourly WS data were at diurnal, monthly and annual scales to capture atmospheric and seasonal influences. The results reveal significant temporal variabilities in WS and WPD, especially over the southern and western coastal and high-altitude regions during the monsoon months (June–August). The spatial analysis revealed a non-linearly increasing trend for WS with altitude, contrary to the simplifying assumptions. Regions such as the Southern Peninsular States (SPSs) and western middle states (WMSs) show high suitability for large-scale deployment, whereas the Northeastern States (NESs) and parts of northern border states (NBS) exhibit lower potential. The site suitability is further evaluated using wind variability indices such as the wind variability index (WVI) and Windy Site Identifier (WSI), along with the plant capacity factor (PCF), cost of energy (COE), and greenhouse gas (GHG) emissions, enabling a comprehensive and decision-oriented framework for wind energy planning. Full article

This study presents the results of a one-month validation campaign focused on wind field reconstruction using a dual-scanning LiDAR configuration. The measurement campaign was conducted inland, approximately 6 km from the Thracian Sea coast in northeastern Greece, and involved the deployment of two scanning LiDAR units alongside a reference meteorological mast. Wind conditions were measured at 82 m above ground level, enabling spatially resolved reconstruction of horizontal wind speed and direction. To investigate the sensitivity of wind field reconstruction to probe volume effects, two range gate length configurations—100 m and 200 m—were systematically alternated during the campaign. This alternating strategy enabled a direct comparison under identical atmospheric conditions. The reconstructed wind speed and direction data exhibited excellent agreement with the reference measurements, achieving a coefficient of determination greater than 0.99, and showed negligible systematic bias. Analysis of turbulence characteristics revealed that the dual-scanning LiDAR system underestimated turbulence intensity compared to the reference meteorological mast. These findings underscore the effectiveness of this technology as a cost-efficient and accurate method for coastal wind characterization. Owing to its ability to reliably reconstruct wind fields over long distances, the system holds strong potential for near-shore and offshore applications. Full article