Search Results (252)

Micro and small wind turbines (MAWTs) are increasingly integrated into residential and prosumer hybrid energy systems. However, their real-world performance often falls short of catalog specifications due to mismatched wind resources, siting limitations, and insufficient attention to human comfort. This paper presents a comprehensive decision-support framework for selecting the type and scale of MAWTs under actual local conditions. The energy assessment module combines aerodynamic performance scaling, wind speed-frequency modeling based on Weibull distributions, turbulence intensity adjustments, and component-level efficiency factors for both horizontal and vertical axis turbines. The framework addresses three key design objectives: efficiency—aligning turbine geometry and control strategies with local wind regimes to maximize energy yield; comfort—evaluating candidate designs for noise emissions, shadow flicker, and visual impact near buildings; and climate adaptation—linking turbine siting, hub height, and rotor type to terrain roughness, turbulence, and built environment characteristics. Case studies from low and moderate wind locations in Central Europe demonstrate how multi-criteria filtering avoids oversizing, improves the autonomy of hybrid PV–wind systems, and identifies configurations that may exceed permissible limits for noise or flicker. The proposed methodology enables evidence-based deployment of MAWTs in decentralized energy systems that balance technical performance, resilience, and occupant well-being. Full article

This research presents an experimental analysis of the influence of atmospheric pressure plasma on the performance of a micro horizontal-axis wind turbine blade. The investigation was conducted using an NACA 4412 airfoil equipped with a dielectric barrier discharge (DBD) plasma actuator. The electrodes were configured asymmetrically, with a 2 mm gap and copper electrodes that are 0.20 mm in thickness. A high voltage of 6 kV was applied, resulting in a current of 0.071 mA and a power output of 0.426 W. Optical emission spectroscopy identified the excited components through the interaction of the high-voltage AC electric field with air molecules: ${\mathrm{N}}_2$, ${\mathrm{N}}_2^{+}$, ${\mathrm{O}}_2^{+}$, and O. The electrohydrodynamic force mainly results from the observed charged ions that, when accelerated by the electric field, transfer momentum to neutral molecules via collisions, leading to the formation of the observed jet plasma. The findings indicated a notable enhancement in aerodynamic performance attributable to the electrohydrodynamic (EHD) flow generated by the plasma. The estimated electrohydrodynamic force ($8.712\times {10}^{-4}$ N) is capable of maintaining the flow attached to the airfoil surface, thereby augmenting flow circulation and, consequently, enhancing the lift force. According to blade element theory, the lift and drag coefficients directly influence the torque and mechanical power generated by the wind turbine rotor. Schlieren imaging was utilized to observe alterations in air density and flow patterns. Lissajous curve analysis was used to examine the electrical discharge behavior, showing that only 7.04% of the input power was converted into heat. This indicates that nearly all input electric energy was transformed into EHD force by the atmospheric pressure plasma. Compared to traditional aerodynamic control methods, DBD actuators are a feasible alternative for small wind turbines due to their lightweight design, absence of moving parts, ability to be surface-embedded without altering blade geometry, and capacity to generate active, dynamic flow control with reduced energy consumption. Full article

Energy generation from renewable sources has increased exponentially worldwide, particularly wind energy, which is converted into electricity through wind turbines. The growing demand for renewable energy has driven the development of horizontal-axis wind turbines with larger dimensions, as the energy captured is proportional to the area swept by the rotor blades. In this context, the dynamic loads typically observed in wind turbine towers include vibrations caused by rotating blades at the top of the tower, wind pressure, and earthquakes (less common). In offshore wind farms, wind turbine towers are also subjected to dynamic loads from waves and ocean currents. Vortex-induced vibration can be an undesirable phenomenon, as it may lead to significant adverse effects on wind turbine structures. This study presents a two-dimensional transient model for a rigid body anchored by a torsional spring subjected to a constant velocity flow. We applied a coupling of the Fourier pseudospectral method (FPM) and immersed boundary method (IBM), referred to in this study as IMERSPEC, for a two-dimensional, incompressible, and isothermal flow with constant properties—the FPM to solve the Navier–Stokes equations, and IBM to represent the geometries. Computational simulations, solved at an aspect ratio of $\varphi =4.0$, were analyzed, considering Reynolds numbers ranging from $Re=150$ to Re = 1000 when the cylinder is stationary, and $Re=250$ when the cylinder is in motion. In addition to evaluating vortex shedding and Strouhal number, the study focuses on the characterization of space–time symmetry during the galloping response. The results show a spatial symmetry breaking in the flow patterns, while the oscillatory motion of the rigid body preserves temporal symmetry. The numerical accuracy suggested that the IMERSPEC methodology can effectively solve complex problems. Moreover, the proposed IMERSPEC approach demonstrates notable advantages over conventional techniques, particularly in terms of spectral accuracy, low numerical diffusion, and ease of implementation for moving boundaries. These features make the model especially efficient and suitable for capturing intricate fluid–structure interactions, offering a promising tool for analyzing wind turbine dynamics and other similar systems. Full article

The increasing deployment of wind energy systems, particularly offshore wind farms, necessitates advanced monitoring and maintenance strategies to ensure optimal performance and minimize downtime. Supervisory Control And Data Acquisition (SCADA) systems have become indispensable tools for monitoring the operational health of wind turbines, generating vast quantities of time series data from various sensors. Anomaly detection techniques applied to this data offer the potential to proactively identify deviations from normal behavior, providing early warning signals of potential component failures. Traditional model-based approaches for fault detection often struggle to capture the complexity and non-linear dynamics of wind turbine systems. This has led to a growing interest in data-driven methods, particularly those leveraging machine learning and deep learning, to address anomaly detection in wind energy applications. This study focuses on the development and application of a semi-supervised, multivariate anomaly detection model for horizontal axis wind turbines. The core of this study lies in Bidirectional Long Short-Term Memory (BI-LSTM) networks, specifically a BI-LSTM autoencoder architecture, to analyze time series data from a SCADA system and automatically detect anomalous behavior that could indicate potential component failures. Moreover, the approach is reinforced by the integration of the Isolation Forest algorithm, which operates in an unsupervised manner to further refine normal behavior by identifying and excluding additional anomalous points in the training set, beyond those already labeled by the data provider. The research utilizes a real-world dataset provided by EDP Renewables, encompassing two years of comprehensive SCADA records collected from a single offshore wind turbine operating in the Gulf of Guinea. Furthermore, the dataset contains the logs of failure events and recorded alarms triggered by the SCADA system across a wide range of subsystems. The paper proposes a multi-modal anomaly detection framework orchestrating an unsupervised module (i.e., decision tree method) with a supervised one (i.e., BI-LSTM AE). The results highlight the efficacy of the BI-LSTM autoencoder in accurately identifying anomalies within the SCADA data that exhibit strong temporal correlation with logged warnings and the actual failure events. The model’s performance is rigorously evaluated using standard machine learning metrics, including precision, recall, F1 Score, and accuracy, all of which demonstrate favorable results. Further analysis is conducted using Cumulative Sum (CUSUM) control charts to gain a deeper understanding of the identified anomalies’ behavior, particularly their persistence and timing leading up to the failures. Full article

This study presents a novel semi-submersible platform design for 10 MW vertical-axis wind turbines (VAWTs), specifically engineered to address the compounded challenges of China’s intermediate-depth (40 m), typhoon-prone maritime environment. Unlike conventional horizontal-axis configurations, VAWTs impose unique demands due to omnidirectional wind reception, high aerodynamic load fluctuations, and substantial self-weight—factors exacerbated by short installation windows and complex hydrodynamic interactions. Through systematic scheme demonstration, we establish the optimal four-column configuration, resolving critical limitations of existing concepts in terms of water depth adaptability, stability, and fabrication economics. The integrated design features central turbine mounting, hexagonal pontoons for enhanced damping, and optimized ballast distribution, achieving a 3400-tonne steel mass (29% reduction vs. benchmarks). Comprehensive performance validation confirms exceptional survivability under 50-year typhoon conditions (Hs = 4.42 m, Uw = 54 m/s), limiting platform tilt to 8.02° (53% of allowable) and nacelle accelerations to 0.10 g (17% of structural limit). Hydrodynamic analysis reveals heave/pitch natural periods > 20 s, avoiding wave resonance (Tp = 7.64 s), while comparative assessment demonstrates 33% lower pitch RAOs than leading horizontal-axis platforms. The design achieves unprecedented synergy of typhoon resilience, motion performance, and cost-efficiency—validated by 29% steel savings—providing a technically and economically viable solution for megawatt-scale VAWT deployment in challenging seas. Full article

As the utilization of wind energy continues to expand as a prominent renewable energy source, the application of Darrieus Vertical Axis Wind Turbine (VAWT) technology has expanded significantly. Various passive modification methods have been developed to enhance efficiency and optimize the aerodynamic performance of the rotor through blade modifications. This study presents passive modification method utilizing Kline–Fogleman (KF) blades which incorporate step-like horizontal slats along the trailing edge. Through Computational Fluid Dynamics (CFD) simulations, this study evaluates ten distinct KF blade configurations, varying in step length and depth, with steps positioned on the inner side, outer side, and both sides of the airfoil. The results indicate that the KF blade with a shorter step on inner side, 20%$c$ in length and 2%$c$ in depth, enhances the average power coefficient ($C_p$) by 19% compared to the rotor with a clean blade. However, when horizontal slats are incorporated on both sides of the blade, with dimensions of 50%$c$ in length and 5%$c$ in depth, $C_p$ decreases by 33% compared to the clean blade. This reduction occurs across both low and high tip speed ratio (TSR) ranges. It has been observed that the presence of a high-pressure zone of 200 Pa at the trailing edge disrupts the aerodynamic performance when the KF blade is in the upwind region between the azimuth angles of 45° and 135°. Full article

The cost of energy generated by large-scale vertical-axis wind turbines faces great challenges for it to be competitive with conventional horizontal-axis wind turbines for offshore deployment. To become competitive, significant reductions in capital cost and operational costs would be competitive. A novel vertical-axis wind turbine that aims to meet these requirements is proposed: the X-rotor wind turbine. An early-stage feasibility study of exemplary two- and three-bladed 5 MW turbines is reported. The cost savings arising from two aspects of the concept that have the greatest impact, namely the power take-off system and O&M, are quantified. Two other aspects that could have a major impact on the cost of energy are the vertical axis rotor and the jacket. The masses for both are evaluated as proxies for their costs. The former costs are determined to be substantial relative to those of conventional HAWTs. Whereas the latter masses are determined not to be prohibitively greater relative to conventional HAWTs. Full article

In this study, a particle image velocimetry (PIV) system was used in a large circulating water tank to investigate the wake of a horizontal-axis tidal turbine model, focusing on minor blockage effects and scale influence. A wake map of the turbine was constructed based on PIV measurements, using velocity deficit, turbulence intensity (TI), and turbulence kinetic energy (TKE) as key indicators. The results showed that TKE developed later than TI, forming a plateau-like shape. This plateau was considered the decay region, with the transition and far-wake regions located before and after it, respectively. Additionally, the power law exponent of TI decreased from −0.731 in the decay region to −0.765 in the far wake, indicating a steeper decay further downstream. Overall, the wake map of the tidal stream turbine model exhibited similarities to that of a previously reported wind turbine model. Full article

One concern in the field of Horizontal Axis Wind Turbines (HAWTs) is what control strategies are needed to handle gust pulses in the wind to prevent extreme oscillations of the blades to reduce fatigue stress, prevent blade rupture, and extend the turbine’s operational life. In order to design innovative control strategies to modify the blade’s oscillatory response, it is crucial to establish the fundamental vibrational behavior of the blades when excited by gust pulses of different frequencies and amplitudes present in the fluctuating wind inflow. In a series of previous works, the authors presented a novel Reduced-Order Characterization (ROC) technique that provided an energy-based characterization of the fundamental modes of oscillation of wind turbine rotors when excited by combinations of wind gust pulses of different frequencies and amplitudes. The main focus of the present work is to extend these original notions of energy-based ROC to a universal technique expressed in terms of non-dimensional quantities that could be applied to turbines of any size, operating in any set of wind conditions, as long as they share geometrical and material similarity. The ROC technique provides a simple formula that is capable of predicting the dominant vibrational modes of a blade with sufficient precision to be useful in the determination of a control decision that can be computed in real time, an aspect of fundamental importance in dealing with rapid fluctuations in wind conditions. Full article

The conversion of air currents through wind turbine technology stands as one of the most significant and effective means of generating green electricity. Wind turbines featuring a horizontal axis exhibit the greatest installed capacity. The study establishes a mathematical model for large wind turbines, categorized by megawatt output, utilizing measured data for key parameters, including wind speed, power output from the generator, and rotational speed. The analysis of the system’s behavior on startup—the cut-in wind speed, is conducted by transitioning the electric generator into motor mode. A mathematical model has been established for the dual-powered motor configuration, wherein both the stator and rotor are connected to a common frequency network, facilitating a shift to synchronous motor functionality. The equation that describes the kinetic moment highlights the importance of attaining optimal velocity, while simultaneously accounting for variations in the load angle. These fluctuations are observable in both the power output and the electrical currents. The simulations that have been processed are derived from experimental data, specifically inputs obtained from a 1.5 MW wind turbine located in the Oravita region of southwestern Romania. The paper thus outlines essential elements concerning the functionality of high-power wind turbines that utilize wound rotor induction generators, aiming to guarantee optimal performance from the moment the wind speed reaches the cut-in threshold. Full article

A numerical study was conducted on winglet designs with multiple sweep angles for improving the performance of horizontal axis wind turbine (HAWT) blades, and their effect on reducing the wing tip vortex was investigated by CFD analysis. The effects of sweep angles were examined through NREL Phase VI turbine blades considering a wind speed range of 7 to 25 m/s. Numerical simulations were performed using RANS equations and the SST k–ω turbulence model. The interaction of the blade rotation and wind flow was modeled using a moving reference frame method. The numerical results were found to be in good agreement with the inferences drawn from the experiments for a baseline blade without a winglet, thereby validating the computational method. The investigations revealed that multi-swept winglets predicted a 14.6% torque increment, providing higher power output than single-swept winglets compared to the baseline blade at a wind speed of 15 m/s. Implementing multiple sweep angles in winglet design can improve the blade performance effectively without further increments in winglet length. Full article

The use of 3D printing is expanding in manufacturing wind turbine blades for renewable energy. This study examines the relationship between geometric parameters, mechanical strength, and aerodynamic performance in blades made from short carbon fiber-reinforced PLA (SCFR-PLA) composites. To achieve this, it includes a comparative evaluation of innovative blade designs and materials, aiming to enhance both the energy efficiency and mechanical durability of horizontal axis wind turbines (HAWTs). The numerical model of the wind turbine blade is validated against experimental results, which employed a NACA geometry and ABS polymer. Building upon this validation, a design of experiments (DOE) analysis is employed to explore the influence of fused filament fabrication (FFF) parameters on the mechanical properties of SCFR-PLA composites. A novel blade design, referred to as HAWTSav, is numerically evaluated using 3D-printed SCFR-PLA composites. Numerical simulations are conducted to evaluate the energy efficiency and structural integrity of the HAWTSav blade. A comparative analysis is then performed, contrasting the performance of the conventional NACA blade in ABS with the HAWTSav blade in SCFR-PLA composites. The findings highlight the potential of SCFR-PLA composites in the development of efficient and durable wind turbine blades, highlighting their applicability, particularly in small-scale wind energy systems. Full article

In the complex and harsh working environment of wind turbines, the horizontal axis wind turbine blade is increasingly confronted with the issue of surface roughening. It leads to a decrease and instability in the output power of the horizontal axis wind turbine. Vortex generator have emerged as a potential solution to this problem by regulating the flow patterns on the blade surface. This research focuses on exploring the impact of vortex generator on the aerodynamic performance of blades under rough wall condition by wind tunnel experiment and computational fluid dynamics simulation. It is important to improve the aerodynamic performance of horizontal axis wind turbine under rough condition. The results show that vortex generator changes the airfoil aerodynamic performance by slowing the stall angle of attack and increasing the ratio of lift-drag in some angles of attack. vortex generator delays the flow separation of the suction surface under the rough wall condition. It is able to counteract the reduction in the aerodynamic performance of blade under rough wall condition. At tip speed ratio is 5.83, vortex generator increased power coefficient by 47.8% under rough wall condition by reducing the flow separation area of 33% radius and weakening the spanwise flow. The study found that the vortex generator effectively eliminated the negative effects of blade surface roughening on aerodynamic performance, improved the roughness insensitivity of the blade, and has good potential for future applications. Full article

Yaw errors occur in wind turbines either during the installation stage or because of the aging of devices. It reduces the wind speed in the rotor axial direction and increases the structural loads in the lateral direction. Diagnosing yaw error rapidly and accurately is crucial for avoiding the introduced under-performance. In this review paper, we first introduce the fundamental concepts and principles of wind turbine yaw control strategies, and we discuss two types of yaw errors (i.e., the static yaw error and the dynamic yaw error) with their corresponding causes. Subsequently, we outline the existing yaw error diagnostic methods, which are based on the LiDAR (light detection and ranging) data, the SCADA (supervisory control and data acquisition) data, or a combination of the two, and we discuss the advantages and disadvantages of various methods. At last, we emphasize that the diagnostic performance can be improved via the combination of the LiDAR data and the SCADA data, and it benefits from an in-depth understanding of the salient features and influential factors associated with the yaw error. Meanwhile, the potential of intelligent clusters and digital twins for detecting yaw errors is discussed. Full article