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A dynamic stall model for tower shadow effects is developed for downwind turbines. Although Munduate’s model shows good agreement with a 1.0 m wind tunnel test model, two problems exist: (1) it does not express load increase before the entrance of the tower wake, and (2) it uses the empirical tower wake model to determine the wind speed profile behind the tower. The present research solves these problems by combining Moriarty’s tower wake model and the entrance condition of the tower wake. Moriarty’s model does not require any empirical parameter other than tower drag coefficient and it expresses positive wind speed around the tower also. Positive wind speed change is also allowed as the tower wake entrance condition in addition to the negative change observed in the previous model. It demonstrates better agreement with a wind tunnel test and contributes to the accuracy of the fatigue load, as it expresses a slight increase in load around the entrance of the tower wake. Furthermore, the scale effects are also evaluated; lift deviation becomes smaller as the scale increases, i.e., lower rotor speed.

A new analysis method to calculate the rotor-induced average tower drag of downwind turbines in the blade element momentum (BEM) method was developed in this study. The method involves two parts: calculation of the wind speed distribution using computational fluid dynamics, with the rotor modeled as a uniform loaded actuator disc, and calculation of the tower drag via the strip theory. The latter calculation considers two parameters, that is, the decrease in wind speed and the pressure gradient caused by the rotor thrust. The present method was validated by a wind tunnel test. Unlike the former BEM, which assumes the tower drag to be constant, the results obtained by the proposed method demonstrate much better agreement with the results of the wind tunnel test, with an accuracy of 30%.

Micro scale wind turbines (μWTs) in the order of 10 kW or less, suffer high vibration levels compared to larger ones. This can be attributed to the fact that they rotate at higher rotational speeds. For simplicity, blades are directly attached to a permanent magnet generator (PMG) of an outer rotor type with no need to install a gearbox. Also due to their small size, a tail vane represents a cost-effective solution for aligning the turbine with the wind direction. Those tail vanes generate significant yaw rates as a consequence of the unpredictable variations in wind direction. High yaw rates, along with increased rotational speeds, generate considerable gyroscopic loads. Therefore, μWTs involve a unique dynamic loading condition. Considering that the existing software packages are primarily designed for large wind turbines, a thorough investigation into the dynamics of μWTs is essential. In this study, we address the peculiarity of dynamics of μWTs using a simple mathematical model that helps in providing better dynamical insights than numerical calculations. Using the mathematical model, a parametric study is conducted involving two parameters: the generator’s bearing span and the position of the rotor’s centre of gravity (CG) along the rotor axis. The parametric study revealed that increasing the bearing span yields a decrease in vibrations. Also, shifting the centre of gravity of the rotor towards the generator’s rear bearing reduces vibrations across all considered degrees of freedom, except for the rotor’s vertical vibrations and pitching, which achieve a minimum value. An optimal placement of the centre of gravity is calculated and used afterwards to improve the design of an existing μWT. A case study highlights this improvement in terms of root mean square vibrations. The presented model can thereby help designers to build μWTs with better performance and longer lifespan offering a better understanding of the dynamical effects of design parameters

Due to the structural aspects of the wind turbine, such as wind shear and tower shadow effects, the output power of the wind turbine has periodic fluctuations, known as 3P fluctuations. These fluctuations can reduce overall power generation and deteriorate power quality. In this context, this paper proposes a power smoothing control method that utilizes rotor inertia and a DC-link capacitor as small-scale energy storage devices. First, the typical energy storage capacities of the rotor’s rotational kinetic energy and the DC-link capacitor’s electrostatic energy are analyzed to assess their smoothing potential. Secondly, a control method is presented to apply the rotor and the DC-link capacitor as small-scale energy storage, with the smoothing frequency range allocated according to their respective storage capacities. Finally, the proposed method is compared with the conventional maximum power point tracking (MPPT) method and the 3P-notch filter method. The effectiveness of the proposed algorithm is verified through MATLAB/Simulink simulations, demonstrating its capability to mitigate periodic power fluctuations. The results showed that the proposed control method is applicable, reliable, and effective in mitigating periodic power fluctuations.

Large-scale wind turbines with a large blade radius rotates under fluctuating conditions depending on the blade position. The wind speed is maximum in the highest point when the blade in the upward position and minimum in the lowest point when the blade in the downward position. The spatial distribution of wind speed, which is known as the wind shear, leads to periodic fluctuations in the turbine rotor, which causes fluctuations in the generator output voltage and power. In addition, the turbine torque is affected by other factors such as tower shadow and turbine inertia. The space between the blade and tower, the tower diameter, and the blade diameter are very critical design factors that should be considered to reduce the output power fluctuations of a wind turbine generator. To model realistic characteristics while considering the critical factors of a wind turbine system, a wind turbine model is implemented using a squirrel-cage induction motor. Since the wind speed is the most important factor in modeling the aerodynamics of wind turbine, an accurate measurement or estimation is essential to have a valid model. This paper estimates the average wind speed, instead of measuring, from the generator power and rotating speed and models the turbine’s aerodynamics, including tower shadow and wind shear components, without having to measure the wind speed at any height. The proposed algorithm overcomes the errors of measuring wind speed in single or multiple locations by estimating the wind speed with estimation error less than 2%.

The comprehensive numerical simulation of the tower shadow effect on floating offshore wind turbines (FOWTs), an area less explored compared to fixed-bottom wind turbines, is presented in this study. The atmospheric boundary layer inflow and the joint north sea wave project random wave are used as the operating conditions for FOWT. The combination of computational fluid dynamics (CFD) software simulator for wind farm applications and turbine simulation tool OpenFAST is used to implement fluid-structure interaction calculations. The output power, platform motion, wake velocity deficit and vortex structures are analyzed to reveal the influence of the tower shadow effect on the FOWT. The results indicate that due to the fluctuation caused by the turbulent wind and the floating platform motion, the tower shadow effect of FOWT is less significant for its periodic power decay than that of fixed-bottom wind turbines. And according to the velocity deficit analysis, the influence area of the tower shadow effect on the wake is mainly in the near wake region.

The aerodynamic performance of the floating offshore wind turbine (FOWT) is obviously affected by the motion of the platform, and becomes much more complicated considering the effect of tower shadow. In view of this, this paper aims at investigating the aerodynamic performance of the floating offshore wind turbine with and without a tower under the three most influential motions (surge, pitch and yaw) by computational fluid dynamic (CFD). The results show that the power of the wind turbine is reduced by 1.58% to 2.47% due to the tower shadow effect under the three motions, and the pressure difference distribution is most obviously interfered by the tower shadow effect under yaw motion and concentrates at the root and tip of the blade. In addition, the degree of interference of the tower shadow effect on the wake flow field is different under the three motions, resulting in a more complex wake structure. These conclusions can provide a theoretical basis and technical reference for the optimal design of floating offshore wind turbines.

The magnitude and stability of power output are two key indices of wind turbines. This study investigates the effects of wind shear and tower shadow on power output in terms of power fluctuation and power loss to estimate the capacity and quality of the power generated by a wind turbine. First, wind speed models, particularly the wind shear model and the tower shadow model, are described in detail. The widely accepted tower shadow model is modified in view of the cone-shaped towers of modern large-scale wind turbines. Power fluctuation and power loss due to wind shear and tower shadow are analyzed by performing theoretical calculations and case analysis within the framework of a modified version of blade element momentum theory. Results indicate that power fluctuation is mainly caused by tower shadow, whereas power loss is primarily induced by wind shear. Under steady wind conditions, power loss can be divided into wind farm loss and rotor loss. Wind farm loss is constant at 3α(3α–1)R2/(8H2). By contrast, rotor loss is strongly influenced by the wind turbine control strategies and wind speed. That is, when the wind speed is measured in a region where a variable-speed controller works, the rotor loss stabilizes around zero, but when the wind speed is measured in a region where the blade pitch controller works, the rotor loss increases as the wind speed intensifies. The results of this study can serve as a reference for accurate power estimation and strategy development to mitigate the fluctuations in aerodynamic loads and power output due to wind shear and tower shadow.

The effects of wind shear and the tower shadow contribute to periodic fluctuations in the wind speed and aerodynamic torque, which cause several problems. This study develops an equivalent wind speed model for large-scale, n -bladed wind turbines that includes the wind shear and the tower shadow effects. The comprehensive model is used to derive the disturbance components of wind speed caused by wind shear, the tower shadow, their synthesis, and the equivalent wind speed and to delineate their spatial distributions in the rotor disk area. Simulation results reveal that the effects of wind shear, the tower shadow, and the equivalent wind speed on the disturbance components fluctuate periodically and are closely related to the wind turbine correlation parameters, such as the rotor radius, hub center height, tower radius, distance from the tower midline to the blade, wind shear exponent, and blade number.

Wind energy has become one of the most promising renewable energy in recent decades. However, severe rotor oscillations arose by the wind shear and tower shadow effects were not only harmful to the power quality but also threatening to the stability of the energy system. Meanwhile, it is difficult to simulate the effects under the local condition. Therefore, it is indispensable to develop an immersion environment for the wind energy conversion. To cover these requirements, a novel approach to simulate the process of the wind energy generation with wind shear and tower shadow effects is presented. In particular, the replication method is applicable to both fixed and variable speed turbines, for the rotor oscillations synchronizing with the rotations at a constant angle. The equivalent wind speed of the effects contributes to the aerodynamics model as nonstationary time series. For stationary processing the nonstationary signals in the time domain, the analysis of computer order tracking is imported to solve the spectral leakage in the fast Fourier transform spectrum. Finally, based on this method, an immersion environment is realized through two coupled induction motors in an electric closure test bed. Experimental results demonstrate that the proposed replication method is effective and accurate in terms of both static and dynamic performances.