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Small wind turbines (SWTs) face tremendous challenges in being developed into a more reliable and widespread energy solution, with a number of efficiency, reliability, and cost issues that are yet to be resolved. As part of the development stages of an SWT, testing the resulting efficiency and determining appropriate working ranges are of high importance. In this paper, a methodology is presented for testing SWTs to obtain characteristic performance curves such as Cp (power coefficient) vs. TSR (tip–speed ratio), and torque vs. ω, in a simpler and faster yet accurate manner as an alternative energy solution when a wind tunnel is not available. The performance curves are obtained with the SWT mounted on a platform moving along a runway, requiring only a few minutes of data acquisition. Furthermore, it is only required to measure a single variable, i.e., the generator output voltage. A suitable physics-based mathematical model for the system allows for deriving the desired performance curves from this set of minimal data. The methodology was demonstrated by testing a prototype SWT developed by the authors. The tested prototype had a permanent magnet synchronous generator, but the methodology can be applied to any type of generator with a suitable mathematical model. Given its level of simplicity, accuracy, low cost, and ease of implementation, the proposed testing method has advantages that are helpful in the development process of SWTs, especially if access to a proper wind tunnel is prevented for any reason. To validate the methodology, Cp vs. TSR curves were obtained for an SWT prototype tested under different test conditions, arriving always at the same curve as would be expected. In this case, the test prototype reached a maximum power coefficient (Cp) of 0.35 for wind velocities from 20 to 50 km/h for a TSR of 5.5.

Onsite utilization of wind energy in the urban environment is an effective solution to environmental protection and energy security. The typically micro wind turbines, including Savonius vertical axis wind turbine, H-type vertical axis wind turbine and micro horizontal axis wind turbine are more suitable for distributed generation, relative to centralized generation of large scale wind turbines. However, the wind in the urban environment characterized by low wind speed, high levels of turbulence and strongly unsteady direction and speed, directly affecting the aerodynamic characteristics of wind turbine. In the present work, wind tunnel tests have been conducted to investigate the low Reynolds number effect on aerodynamic characteristics for these three typical micro wind turbines, and the aerodynamic differences among them have been compared qualitatively and quantitatively. The experimental results show that micro horizontal axis wind turbine and H-type vertical axis wind turbine, belonging to lift-type wind turbine, have relatively higher startup wind speed and lower power coefficient due to deteriorative aerodynamic performance of airfoil at low wind speed. However, Savonius vertical axis wind turbine, as a drag-type wind turbine, exhibits excellent aerodynamic performance at low Reynolds number. The Savonius wind turbine has apparent output power at 5m/s, and the peak power coefficient exceeding 0.2 at 9m/s being superior to that of two other lift-type wind turbines at the same wind speed. In addition, in consideration of natural advantage of vertical axis wind turbine, Savonius wind turbine is the best option for applying at low Reynolds number urban environment.

From the viewpoint of installing small wind turbines (SWTs) on rooftops, this study investigated the effects of wind direction and horizontal aspect ratio (HAR = width/length) of a high-rise cuboid building on wind conditions above the roof by conducting large eddy simulations (LESs). The LES results confirmed that as HAR decreases (i.e., as the building width decreases), the variation in wind velocity over the roof tends to decrease. This tendency is more prominent as the angle between the wind direction and the normal vector of the building’s leeward face with longer roof edge increases. Moreover, at windward corners of the roof, wind conditions are generally favorable at relatively low heights. In contrast, at the midpoint of the roof's windward edge, wind conditions are generally not favorable at relatively low heights. At leeward representative locations of the roof, the bottoms of the height range of favorable wind conditions are typically higher than those at the windward representative locations, but the favorable wind conditions are much better at the leeward representative locations. When there is no prevailing wind direction, the center of the roof is more favorable for installing SWTs than the corners or the edge midpoints of the roof.

It is well known that the output power from small wind turbines (SWTs) fluctuates noticeably more when compared to that from other types of dispersed generators, such as residential photovoltaic (PV) power generation systems. Thus, the degradation of voltage quality, such as flicker emissions, when numerous SWTs are installed in a low-voltage distribution system is a particular concern. Nevertheless, practical examples of flicker emissions from small wind power facilities have not been made public. This paper aims to clarify the characteristics of flicker emissions by SWTs and their severity. The measurement results at the two selected sites indicate that the flicker emissions solely caused by variable-speed SWTs with a total power rating of ~20 kW are notably lower than the upper limit, and they are at their highest when the mean total output power is approximately 3/4 of the total power rating of small wind power facilities.

Blade element momentum theory continues to be widely used in the wind industry to calculate and analyze wind turbines. This theory has been improved many times to address its inherent weakness of convergence capability. This article applies the one variable BEM method, which has been further improved to help ensure convergence to apply analytical calculations for small horizontal-axis straight-blade wind turbines. This type of turbine has much potential for practical applications, providing electricity to households and residential areas far from cities, but has not been fully researched. Straight-blade turbines with relatively large Re changes in blade spanwise direction often cause difficulties in the convergence of BEM algorithms. This article presents the ability to apply improved BEM theory to straight-blade wind turbines in the wind speed range from 5 to 7 m/s and tip speed ratio from 4 to 7 through analytical calculations. A well-validated CFD model was also performed to evaluate the reliability of the calculation method. The obtained results show that the improved BEM method can be applied to calculate the mechanical power output of straight-blade turbines with errors of less than 10% compared to reality. This thereby proves the applicability of the improved BEM method to solve practical problems of small wind turbines.

The type of airfoil with small wind turbine blades should be selected based on the wind potential of the area in which the turbine is used. In this study, 10 low Reynolds number airfoils, namely, BW-3, E387, FX 63-137, S822, S834, SD7062, SG6040, SG6043, SG6051, and USNPS4, were selected and their performance was evaluated in a 1 kW wind turbine in terms of the power coefficient and also the startup time, by performing a multi-objective optimization study. The blade element momentum technique was utilized to perform the calculations of the power coefficient and startup time and the differential evolution algorithm was employed to carry out the optimization. The results reveal that the type of airfoil used in the turbine blade, aside from the aerodynamic performance, completely affects the turbine startup performance. The SG6043 airfoil has the highest power coefficient and the BW-3 airfoil presents the shortest startup time. The high lift-to-drag ratio of the SG6043 airfoil and the low inertia of the turbine blades fitted with the BW-3 airfoil make them suitable for operation in windy regions and areas with low wind speeds, respectively.

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated for anomaly detection on wind turbine blades, including Xception, Resnet-50, AlexNet, and VGG-19, along with a custom convolutional neural network. For further analysis, transfer learning approaches were also proposed and developed, utilizing these architectures as the feature extraction layers. In order to investigate model performance, a new dataset containing 6000 RGB images was created, making use of indoor and outdoor images of a small wind turbine with healthy and damaged blades. Each model was tuned using different layers, image augmentations, and hyperparameter tuning to achieve optimal performance. The results showed that the proposed Transfer Xception outperformed other architectures by attaining 99.92% accuracy on the test data of this dataset. Furthermore, the performance of the investigated models was compared on a dataset containing faulty and healthy images of large-scale wind turbine blades. In this case, our results indicated that the best-performing model was also the proposed Transfer Xception, which achieved 100% accuracy on the test data. These accuracies show promising results in the adoption of machine learning for wind turbine blade fault identification.

Wind turbine blades perform the most important function in the wind energy conversion process. It plays the most vital role of absorbing the kinetic energy of the wind, and converting it to mechanical energy before it is transformed into electrical energy by generators. In this work, National Advisory Committee for Aeronautics (NACA) 4412 and SG6043 airfoils were selected to design a small horizontal axis variable speed wind turbine blade for harvesting efficient energy from low wind speed areas. Due to the low wind profile of the targeted area, a blade of one-meter radius was considered in this study. To attain the set objectives of fast starting time and generate more torque and power at low wind speeds, optimization was carryout by varying Reynolds numbers (Re) on tip speed ratios (TSR) values of 4, 5, and 6. The blade element momentum (BEM) method was developed in MATLAB programming code to iteratively find the best twist and chord distributions along the one-meter blade length for each Re and tip speed ratio (TSR) value. To further enhance the blade performance, the twist and chord distributions were transferred to Q-blade software, where simulations of the power coefficients (Cp) were performed and further optimized by varying the angles of attack. The highest power coefficients values of 0.42, 0.43, and 0.44 were recorded with NACA 4412 rotor blades, and 0.43, 0.44, and 0.45 with SG6043 rotor blades. At the Re of 3.0 × 105, the blades were able to harvest maximum power of 144.73 watts (W), 159.69 W, and 201.04 W with the NACA 4412 and 213.15 W, 226.44 W, 245.09 W with the SG6043 at the TSR of 4, 5, and 6 respectively. The lowest cut-in speed of 1.80 m/s and 1.70 m/s were achieved with NACA 4412 and SG6043 airfoils at TSR 4. At a low wind speed of 4 m/s, the blades were able to harness an efficient power of 79.3. W and 80.10 W with both rotor blades at the TSR 4 and 6 accordingly.

The efficiency of energy conversion from wind to mechanical energy of a rotating wind turbine rotor depends on the flow conditions of the medium and its impact on the rotor blade. Flow conditions change with change in wind speed and rotor rotational speed. Therefore, in order to increase the operating area of a wind turbine with good efficiency values, it is necessary to modify the turbine blade setting. Mechanical solutions for changing the pitch setting of turbine blades exist for large wind turbine rotors. For small wind turbines, such systems are not used due to the system's costs, which significantly increase the cost of a small turbine. Therefore, it is necessary to develop a solution that will be cheap to use and will ensure an improvement in the efficiency of a small wind turbine. The article discusses analysis of turbine blade deformation caused by centrifugal force. Deformation analyses of the blade with the proposed structure were carried out in numerical tests, and the results are presented in the article. The simulations and obtained results indicate the key role of turbine blade cross-section stiffness. Furthermore, they indicate the need for further work to investigate the relationship between blade stiffness, cross-section geometry, and blade wall thickness.

This paper provides three different research contributions applied to a Wind Turbine patented in 1606 by the inventor Jerónimo de Ayanz y Beaumont. The windmill under study is the Ayanz Wind Turbine with screw blades. The first contribution consists of an experimental characterization of the Ayanz Wind Turbine, incorporating the enclosure proposed at the patent and showing that the efficiency of the wind turbine is increased between 70% and 90% due to the enclosure being employed. As not many details about the shape of the screw blades are provided at the patent, in this article the nowadays well-studied and commercially available Archimedes Spiral Wind Turbine blade is utilized. It has been observed that by using an enclosure with a cylindrical shape, not only the efficiency of the wind turbine is increased, but the visual impact is reduced as seeing the blades rotating is avoided, which is a very important fact for many potential individual users of this wind turbine. In addition, it also enables the use of a protective mesh for birds, almost totally reducing the probability of bird deaths. The second contribution consists in a simple and low-cost Maximum Power Point Tracking (MPPT) strategy for the wind turbine, which only uses an AC three-phase impedance to capture the maximum energy from the wind, enabling to eliminate the DC-DC converter and microprocessor employed typically for this purpose. Due to this, the cost, complexity, failure rate, and power losses of the electronic power circuit are reduced which is very welcomed for small-scale wind turbines. Finally, the last contribution is a protection electronic circuit that fulfills several objectives: to brake the wind turbine under high winds and to disconnect and protect it when over-currents occur and when the voltage range of the batteries connected to the wind turbine is outside their safety range.