Extreme-size wind turbines face logistical challenges due to their sheer size. A solution, segmentation, is examined for an extreme-scale 50 MW wind turbine with 250 m blades using a systematic approach. Segmentation poses challenges regarding minimizing joint mass, transferring loads between segments and logistics. We investigate the feasibility of segmenting a 250 m blade by developing design methods and analyzing the impact of segmentation on the blade mass and blade frequencies. This investigation considers various variables such as joint types (bolted and bonded), adhesive materials, joint locations, number of joints and taper ratios (ply dropping). Segmentation increases blade mass by 4.1%–62% with bolted joints and by 0.4%–3.6% with bonded joints for taper ratios up to 1:10. Cases with large mass growth significantly reduce blade frequencies potentially challenging the control design. We show that segmentation of an extreme-scale blade is possible but mass reduction is necessary to improve its feasibility.
Off-grid users can be provided with electricity via a hybrid integration of wind power generators and a diesel system functioning as a backup supply. However, due to wind power fluctuations and rapid load changes, system voltage and frequency variances may exceed permitted limits, resulting in aberrant system behavior. Therefore, to improve the dynamic performance of the wind-diesel power system, a hybrid energy storage system (HESS) made of battery and superconducting magnetic energy storage is installed with the system via a converter interface. Based on the switching manifold design, a sliding mode controller with the super-twisting feature is developed over the hybrid energy storage system (HESS) to carry out the required amount of power exchanges with the system accomplished through the control of converter operation. Lyapunov stability analysis is conducted to guarantee the asymptotic stability of the system. MATLAB simulations are performed to validate the improved performance of the system with the proposed scheme.
One of the important challenges for Vertical Axis Wind Turbine (VAWT) is to fully understand its dynamic characteristics in different operating conditions. Meanwhile, it is necessary to seek a fast and accurate method to evaluate the dynamic characteristic of VAWT. In this study, we improve the LB model by considering the operating principle of VAWT to study the dynamic characteristics of the dedicated and commonly used VAWT airfoils in different operating conditions. The results show that the improved LB model is suitable for simulating the dynamic characteristic of VAWT with a thick airfoil. Although the asymmetric airfoil shows the higher lift coefficient, their dynamic characteristic appears huge fluctuation as the increases of tip speed ratio. Moreover, at a low tip speed ratio, the advantages of the asymmetric airfoil are not obvious. While the dynamic characteristic of the symmetric airfoil is relatively stable with the variation of tip speed ratio.
The public road setback distance is often an important factor that drives wind farm design. This paper outlines a methodology for assessing the risk imposed by blade throw at various road setbacks using a physics-based simulation approach. Given a road setback distance, Monte Carlo simulation is performed wherein blade throw parameters and vehicle locations are randomized. Potential collisions are determined using an “impact circle” approach which assumes that impact occurs if the vehicle is inside the impact radius of the blade fragment when it lands. This approach is exercised on several example turbines and risk levels are calculated for various road setbacks. The method is also applied to a notional wind farm with turbines located at a typical road setback distance. Results show that the blade throw risk imposed to vehicles on public roads for the example wind farm is extremely small and commensurate with risks imposed by everyday activities.
There are few reports in the literature regarding wind speed near the ground. This work presents a model for wind speed from 4 m above the ground, based on year-round measurements in two meteorological towers. Each tower is equipped with anemometers at five heights, as well as thermometers and pressure and relative humidity sensors. The data is processed using Eureqa artificial intelligence software, which determines the functional relationship between variables using an evolutionary search technique called symbolic regression. Using this technique, models are found for each month under study, in which height and temperature are the variables that most affect wind speed. The model that best predicts the measured wind speeds is then selected. A polynomial function directly proportional to height and temperature is identified as the one that provides the best predictions of wind speed on average, within the rough sub-layer. Finally, future work is identified on testing the model at other locations.
A total of 27 test profiles from the IEC 61400-1 design load cases were tested using a 7.5-MW wind turbine drivetrain test bench and two multi-megawatt wind turbine drivetrains. Each test profile consisted of simultaneous vertical, lateral, and longitudinal forces, yawing and nodding bending moment, and rotational speed. These test-bench inputs were compared with the forces, bending moments, and speed that were applied to the wind turbine drivetrains to quantify the test-bench tracking error. This tracking error was quantified for a range of ramp-rate limits of the yawing and nodding bending moments. The experimental results were compared with predictions from an evaluation method for the capability of wind turbine drivetrain test benches to replicate dynamic loads. The method’s predictive capability was found to be sufficient for the goal of early screening and its formulation is applicable to any wind turbine drivetrain test bench and drivetrain design.
The growth rate of offshore wind is increasing due to technological advancement and reduction in cost. An approach using mast measured data at coastline and reanalysis data is proposed for offshore wind resource assessment, especially for developing countries. The evaluation of fifth generation European Reanalysis (ERA5) data was performed against measured data using statistical analysis. ERA5 data slightly underestimates wind speed and wind direction with percentage bias of less than 1%. Wind resource assessment of region in Exclusive Economic Zone (EEZ) of Pakistan was performed in terms of wind speed and Wind Power Density (WPD). The range of monthly mean wind speed and WPD in the region was 4.03–8.67 m/second and 73–515 W/m2 respectively. Most-probable wind speed and dominating wind direction on corners and center of the region were found using probability distributions and wind rose diagrams respectively. Most-probable wind speed ranges 4.41–7.64 m/second and dominating wind direction is southwest.
The study presented in this paper concerns the development of a new methodology for design and controlling a wind energy generation chain. This methodology is based on combined Analytical-Finite Element-Experimental method. This type of converter chosen is an AC-DC inverter with IGBTs to improve the robustness of the power chain structure. It offers a reduction of the cost of the power chain and the improvement of the performances of the global studied system, as the control at power factor equal to unity and providing an electromagnetic torque which is added to the useful torque in order to extract the maximal energy. The control algorithms permit to regulate Le charging voltage and current in their rated values considered as optimal battery charging voltage and current. The global model of the power chain is implemented under the Matlab-Sumilink simulation environment for performance and efficiency analysis.
Vertical Axis Wind Turbine (VAWT) can be a promising solution for electricity production in remote ice prone territories of high north, where good wind resources are available, but icing is a challenge that can affect its optimum operation. A lot of research has been made to study the icing effects on the conventional horizontal axis wind turbines, but the literature about vertical axis wind turbines operating in icing conditions is still scarce, despite the importance of this topic. This paper presents a review study about existing knowledge of VAWT operation in icing condition. Focus has been made in better understanding of ice accretion physics along VAWT blades and methods to detect and mitigate icing effects.
Models of a wind energy conversion chain using classical Simulink models of a diode bridge exhibit significant simulation time making difficult its combination with large scales optimization approaches. For this purpose and to increase the degree of compatibility of wind turbine models with large scales optimization approaches such as those based on Genetic Algorithms, a wind energy conversion system having an horizontal axis propeller, an axial generator with permanent magnets, recharging a battery energy accumulator through a diode rectifier is modeled by simplified method reducing simulation time. Indeed, a model of the three phase’s diode rectifier making the simulation time considerably reduced compared to the existing model in the Simulink library is developed. This model is validated by comparison with the model using the classic Simulink library. Another objective of this study is the formulation of the useful torque optimization problem having an essential constraint the reduction of the generator phase’s inductance in the goal to reduce the overvoltage in generator phases.