Wind Turbine Power Generation Research Articles

Aerodynamic optimization of the configuration of a pair of vertical axis wind turbines

This study optimized the layout of a pair of Darrieus vertical axis wind turbines through three-dimensional computational fluid dynamics (CFD) simulations. Three design parameters including the horizontal distance between the axes of two wind turbines (S), the vertical distance between the mid-heights of two wind turbines (h), and the orientation of two wind turbines with respect to the incoming wind (β) were studied. A design of experiment method and a single objective optimization algorithm based on the Taguchi’s method were employed to determine the optimum design parameters that maximize the power output of paired wind turbines. Analyzing the results showed that for all the numerical experiments, the power generation of paired wind turbines was more than that of a single wind turbine. In addition, it was realized that the vertical distance between the mid-heights of two wind turbines had the most influence and the horizontal distance between the axes of two wind turbines had the least impact on the average coefficient of power of paired wind turbines. The power output of paired wind turbines was maximum when wind turbines were placed at the same height and reduced significantly when there was a height difference. The power generation of paired wind turbines improved slightly by decreasing the horizontal distance between the axes of two wind turbines. The extent of impact of design parameters ordered as h>β>S. The optimum values of the design parameters were determined to be β=90°, h=0, and S=1.5 turbine diameters. Therefore, the power generation of paired wind turbines was maximum when wind turbines were placed side-by-side, at the same height, and at the smallest horizontal distance. It was revealed that for the optimum configuration, the power output of paired wind turbines improved by 26.60% with respect to that of a single wind turbine.

The effect of reduced power operation of faulty wind turbines on the total power generation for different wind speeds

High failure rates have greatly limited the development of the wind power industry. Improving the operation and maintenance of wind turbines can help resolve this problem. Research in this area has thus far focused on the early detection of faults and the prediction of the remaining useful life of wind turbines and has rarely discussed remedies following failure. Currently, wind turbines are shut down for maintenance immediately after the occurrence of a failure, often resulting in large downtimes. However, this is not always necessary since turbines can continue to operate with a reduced power output to improve the total power generation. In this study, the continuous operation time after fault detection is calculated by principal component analysis, and its effectiveness is verified. The effect of reduced power operation on the continuous operation time and the total power generation of wind turbines is analyzed. Finally, the effect of wind speed on reduced power operation is analyzed. The results show that reduced power operation can prolong operational time and increase the total power generation of a wind turbine.

Turbulence time scale equally important as intensity to wind turbine power generation

Measurements of a model wind turbine confirm previous results from the field

Effect of wind veer on wind turbine power generation

Wind direction variation with height (wind veer) plays an essential role in the inflow wind field as the wind turbine enlarges. We explore the wind veer characteristics and their impact on turbine performance using a 5-year field dataset measured at the Eolos Wind Energy Research Station of the University of Minnesota. Wind veer exhibits an appreciable diurnal variation that veering and backing winds tend to occur during nighttime and daytime, respectively. We further propose to divide the wind veer conditions into four scenarios based on their changes in turbine upper and lower rotors that influence the loading on different rotor sections: VV (upper rotor: veering, lower rotor: veering), VB (upper rotor: veering, lower rotor: backing), BV (upper rotor: backing, lower rotor: veering), and BB (upper rotor: backing, lower rotor: backing). Such a division allows us to elucidate better the impact of wind veer on turbine power generation. The clockwise-rotating turbines tend to yield substantial power losses in scenarios VV and VB and small power gains in scenarios BV and BB. The counterclockwise-rotating turbines follow exactly opposite trends to the clockwise turbine. The derived findings are generalizable to other wind sites for power evaluation and provide insights into the turbine type selections targeting the maximum profits.

Study and Simulation of a Wind Hydro Isolated Microgrid

Isolated microgrids are microgrids which operate autonomously. This paper presents an isolated microgrid which combines a Hydraulic Turbine Generator (HTG) with a Wind Turbine Generator (WTG) to supply consumers forming a Wind Hydro Isolated Microgrid (WHIM). The WHIM includes a Dump Load (DL) to dissipate the active power excess. The WHIM has been modeled and its operation has been simulated in two modes: Wind-Hydro (WH), where both HTG and WTG supply power, and Wind-Only (WO) mode, where the WTG is the active power supplier and the HTG keeps connected to the grid with null power to generate the grid voltage. In WO, a fast frequency regulation is achieved by means of a controller which commands the DL to consume the WTG power excess. Additionally, the simulation of the mode transition from WO to WH, which is triggered by a system active power deficit in WO mode, is shown. A kick starting system designed to speed up the HTG power production improves the transient from WO to WH mode change. Finally, the simulations in WH mode show the interaction between the HTG and WTG. The two controls proposed have been proved effective and the simulations show a good WHIM dynamic performance.

Prediction of power generation and rotor angular speed of a small wind turbine equipped to a controllable duct using artificial neural network and multiple linear regression

Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.

Development and Validation of CFD 2D Models for the Simulation of Micro H-Darrieus Turbines Subjected to High Boundary Layer Instabilities

The simulation of very small vertical axis wind turbines is often a complex task due to the very low Reynolds number effects and the strong unsteadiness related to the rotor operation. Moreover, the high boundary layer instabilities, which affect these turbines, strongly limits their efficiency compared to micro horizontal axis wind turbines. However, as the scientific interest toward micro wind turbine power generation is growing for powering small stand-alone devices, Vertical Axis Wind Turbines (VAWTs)might be very suitable for this kind of application as well. Furthermore, micro wind turbines are widely used for wind tunnel testing, as the wind tunnel dimensions are usually quite limited. In order to obtain a better comprehension of the fluid dynamics of such micro rotors, in the present paper the authors demonstrate how to develop an accurate CFD 2D model of a micro H-Darrieus wind turbine, inherently characterized by highly unstable operating conditions. The rotor was tested in the subsonic wind tunnel, owned by the University of Catania, in order to obtain the experimental validation of the numerical model. The modeling methodology was developed by means of an accurate grid and time step sensitivity study and by comparing different approaches for the turbulence closure. The hybrid LES/RANS Delayed Detached Eddy Simulation, coupled to a transition model, demonstrated superior accuracy compared to the most advanced unsteady RANS models. Therefore, the CFD 2D model developed in this work allowed for a thorough insight into the unstable fluid dynamic operating conditions of micro VAWTs, leading the way for the performance improvement of such rotors.

Robust frequency control in a wind-diesel autonomous microgrid: A novel two-level control approach

Volatile nature in renewable power output, stochastic nature of load and continuous change in system structure are the key factors affecting the stable operation of microgrid (MG), particularly in frequency control. Appropriate control schemes are indispensable to reduce the frequency fluctuations in MG under such scenarios. Concerning to these issues; this paper proposes a novel two-level control mechanism approach to mitigate the frequency fluctuations in the wind-diesel standalone MG. In the first level, from wind turbine generator (WTG) side, a fixed wind power command is replaced by an optimum adaptive wind power command based on the power system operating conditions and wind speed conditions. To perform this task, the fuzzy logic approach (FLA) is employed by considering change in wind velocity and frequency deviation as inputs and change in WTG power as output. In the second level, a robust FLA tuned Proportional Integral (PI) controller is proposed to regulate the output power of the diesel engine generator (DEG) for the further reduction in MG frequency fluctuations. With this proposed two-level approach, the MG frequency fluctuations are within the limits in all possible operating conditions, which include some critical operating scenarios. Moreover, the superiority of proposed approach in dynamic performance enhancement against load and wind power changes is proven by comparing with various powerful controllers in the literature.

Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear

The power generation of wind turbines varies depending on external environmental conditions. To present universal correlations between conditions that affect wind speed and wind turbine power, this study analyzed the effects of three atmospheric factors—atmospheric stability, turbulence intensity (TI), and wind shear exponent (WSE)—on the power performance and annual energy production (AEP) of wind turbines. Additionally, the horizontal and vertical speed components of the 3D sonic anemometer were investigated. At two measurement heights, unstable regimes showed an ascending air current, whereas stable regimes simultaneously showed both ascending and descending currents. Power curves calculated for each atmospheric factor regime revealed that atmospheric stability (200 kW–11 m/s) exhibited the greatest difference, followed by TI (91 kW–11 m/s) and WSE (32 kW–10.5 m/s). Finally, AEP was calculated at the annual mean wind speed of the study site and exhibited variations of 1.4–4% according to the factor regime. The AEP difference due to the change in atmospheric stability was greatest, and AEP was highest in moderately unstable atmospheric conditions. Clearer understanding of the effects of atmospheric factors on the power characteristics and AEP of wind turbines is expected to deliver practical benefits for wind-resource assessment and power-production prediction.

Wind turbine power modelling and optimization using artificial neural network with wind field experimental data

The wake effect is a major and complex problem in the wind power industry. Wake steering, such as controlling yaw angles of wind turbines, is a proven approach to mitigate the wake influence and increase the power generation of a wind farm. This paper proposes a power prediction model and optimizes yaw angles to minimize the entire wake impact on wind turbines. The power model adopts the artificial neural network (ANN)with the consideration of the wake effect, so it is called ANN-wake-power model. The model can estimate the total power generation of wind turbines for given wind speeds, wind directions, and yaw angles. A case study has been conducted to introduce the modelling process. The experimental data of five wind turbines from an operating wind farm have been used to train and evaluate the model. The ANN-wake-power model has proven to be effective in estimating the power generation. It performs a good balance between computational cost and accuracy. Subsequently, the model is applied to optimize the yaw angles by using Genetic Algorithm. With the optimized yaw angle strategy, the total power ratio of wind turbines can reach 0.96 in all directions involved. For a row of wind turbines, the optimal yaw control strategy for each wind turbine is different. Finally, it is worth noting that, to achieve a good performance of the ANN-wake-power model, sufficient input data should be adopted in the training process.

Economic power control for offshore wind farms with loop connection cables

Abstract The Canadian developer and owner of green power facilities Northland Power Inc. owns two offshore wind farms (OWFs) in the German Bight, Deutsche Bucht and Nordsee One, operated by the subsidiary Northland Power Europe GmbH. The company supports and conducts research in the field of power flow optimization in wind farm networks. The work at hand represents the results of this effort to maximize the efficiency of the assets. The project was accomplished within a cooperation between the Nordsee One GmbH and the Institute of Electrical Power and Energy Technology at the Hamburg University of Technology. From an external point of view, an OWF represents an “en bloc” power plant connected to the onshore transmission grid via power export cables. Nevertheless, such a power plant comprises a complex, large-scale internal medium voltage network. In case of failure or cable outage, the network topology of an OWF may be modified and unintended overloading of inter-array cables (IACs) is possible. In order to address this issue, a new algorithm and software tool for economic power control in OWFs are introduced in the following which can be employed in wind farms with integrated loop connection cables (LCCs). This configuration particularly entails the risk of overloading cable segments depending on the present wind speed. The new algorithm provides the operator with adapted active power setpoints for each wind turbine generator (WTG) in a given network topology. The aim is to maximize OWF power generation and minimize internal power losses while secure network operation is guaranteed. Using load flow analysis based on WTG power output measurements, the load on each cable section is monitored and the cables can be utilized to their individual full capacity while overload is avoided. The practicability of the approach is demonstrated by means of simulation results.

Improving wind turbine efficiency through detection and calibration of yaw misalignment

Abstract Yaw misalignment has a serious impact on energy capture, power quality and health status of wind turbine. However, most detection and calibration methods require additional equipment and the detection results are seriously disturbed by the complex working conditions. In this paper, two types of typical yaw misalignments are defined at first. A new simulation method is applied to simulate the power outputs in different yaw states. Based on the simulation data, a detailed analysis of yaw misalignment effect on Wind Turbine Power Generation (WTPG) is made subsequently, and we find that different yaw misalignments have coupling effects on WTPG. According to the theoretical analysis, an improved yaw misalignment detection method based on Maximum Power Capture (MPC) is proposed, and only SCADA data is used as the model input. After detection, yaw misalignments can be easily calibrated without manual operation. Both simulation data and measured data of multiple wind turbines are used to evaluate the model performance. The results show that the proposed method can improve the efficiency of horizontal axis wind turbines by detecting and calibrating of yaw misalignment, and it has stronger robustness and wider applicability compared with other data-dirven methods.

Use of aerogenerators for alternative electricity production: adaptations and challenges in manaus company

The combination of tools and the possibility of arranging mechanisms that prove to be sustainable and aimed at meeting a certain environmentally correct demand is a challenge today, as it depends on the perception of professionals in charge of implementing changes in conventional systems. Ensuring that the precepts of energy production are shaped bringing more efficiency, also implies the impact on the environment, be it small, medium or large, certainly, that actions that reduce this impact corroborate for new conducts and other applications. An aerogenerator system is a device capable of generating energy by the force of the winds, which mobilizes the blades, whose movement can be reused to aerate environments. What brings the expectation of the speed gain generated in the blades of the system, can be passive of other uses, this aspect can turn into advantages, because these subsidies would be wasted if they were used independently they would be wasted. This work is part of a construction of a system implanted in a factory in the Industrial District of Manaus, using a 500 Watt wind turbine for power generation, where the system was adapted to an extractor in the factory's Cafeteria for presenting a slab that facilitated the installation. The idealization of a combination of instruments that will compose a matrix capable of acting with sustainability, the methodology consists of creating a mechanism of reordering a structure to maintain itself with sustainability, with a bibliographic survey on the impact conditions of the use of materials for power generation, combining fundamentals for the application of the generated by-products.

A Multi-Fault Detection Method With Improved Triplet Loss Based on Hard Sample Mining

Fault detection plays an essential role in the power generation of wind turbines (WTs). However, most of the present fault detection methods are designed to detect a certain type of fault. When these methods are used to detect multiple fault types, their accuracies tend to decline. In this paper, an effective multi-fault detection method based on improved triplet loss is proposed. First, a hard sample mining method is presented based on WT data for the first time, so that the samples which are more suitable for triplet training are selected. Second, triplet training is improved by applying a new mapping layer and optimizing the loss function. Third, based on the improved triplet training, a deep learning model is trained to map the original samples into feature vectors in an embedding space, so that the distance between two samples in the same class is shortened whereas that of different classes is lengthened. Then, a multi-classification model is trained to distinguish the feature vectors, so that the faults of different types can be detected. Finally, four groups of experiments are conducted using real WT SCADA data collected from a wind farm in northern China. The experiment results show that the proposed method is effective.

Modeling and Analysis of a Deflection Type Permanent Magnet Synchronous Wind Generator System

A novel type of multi-degree-of-freedom (multi-DOF) deflecting-type permanent-magnet synchronous wind generator (PMSWG) is constructed to improve the reliability and utilization of wind energy. The basic working principle of the multi-DOF deflecting-type permanent-magnet synchronous generator (PMSG) is introduced, and its structural size is experimentally and theoretically determined. Subsequently, the multi-DOF deflecting-type PMSG was used to operate a complete wind turbine. A prototype and three-dimensional (3D) model of the wind turbine is simulated, allowing one to analyze the aerodynamics of the turbine and power generation performance. The electromagnetic field analysis is performed via analytical methods, followed by a 3D finite element and torque analyses. Furthermore, the wind turbine power generation characteristics curves are obtained through simulation software. Finally, transient analysis of post deflection is demonstrated. The before and after deflection values of the generator voltage, current, flux linkage, and induced voltage are compared and analyzed, relying on simulations and experiments. Additionally, the wind tunnel experiment is used to compare voltage variation with wind direction. The comparison reveals that the wind generator phase voltage remains maximized with wind direction variation. The results confirm that the proposed PMSWG has excellent performance and future research potential.

Modeling and Control Design of an Autonomous Hybrid Wind/Energy Storage Generation Unit

The purpose of the present paper is to investigate a controller design and simulations of autonomous hybrid wind turbine system with variable-speed permanent magnet synchronous generator (PMSG) and a system for storing energy. The proposed system is mainly composed of a wind turbine drives permanent magnet synchronous generator, uncontrolled rectifier, DC/DC converter, DC/AC inverter and static loads. Furthermore, the mathematical model of the studied sub-systems and two control loops are considered. The first one is the controller which needed to preserve the DC-link voltage fixed at its desired value. The second one is the controller which needed to regulate the charge/discharge modes of the storage battery. The suggested hybrid wind/energy storage power generation model is considered and analyzed in case of without controller firstly. Then, the considered hybrid wind/energy storage power generation unit with the proposed controller is examined through a step change in wind speed. Digital simulation results show that the power desired by the linked loads may be successfully supplied and transported by the presented hybrid wind turbine and energy storage power generation system based on proportional-integral-derivative (PID) controller. Also, the emulation results show that there a good foretelling of the electrical variable waveforms and good achievement in case of the presented controller emulated with the case of without controller as maintaining the load voltage fixed at its reference values

Development of High Performance Airfoils for Application in Small Wind Turbine Power Generation

Small wind turbine power generation systems have the potential to meet the electricity demand of the residential sector in developing countries. However, due to their exposure to low Reynolds number (Re) flow conditions and associated problems, specific airfoils are required for the design of their blades. In this research, XFOIL was used to develop and test three high performance airfoils (EYO7-8, EYO8-8, and EYO9-8) for small wind turbine application. The airfoils were subsequently used in conjunction with Blade Element Momentum Theory to develop and test 3-bladed 6 m diameter wind turbine rotors. The aerodynamic performance parameters of the airfoils tested were lift, drag, lift-to-drag ratio, and stall angle. At Re=300,000, EYO7-8, EYO8-8, and EYO9-8 had maximum lift-to-drag ratios of 134, 131, and 127, respectively, and maximum lift coefficients of 1.77, 1.81, and 1.81, respectively. The stall angles were 12° for EYO7-8, 14° for EYO8-8, and 15° for EYO9-8. Together, the new airfoils compared favourably with other existing low Re airfoils and are suitable for the design of small wind turbine blades. Analysis of the results showed that the performance improvement of the EYO-Series airfoils is as a result of the design optimization that employed an optimal thickness-to-camber ratio (t/c) in the range of 0.85–1.50. Preliminary wind turbine rotor analysis also showed that the EYO7-8, EYO8-8, and EYO9-8 rotors had maximum power coefficients of 0.371, 0.366, and 0.358, respectively.

Quantification of parameter uncertainty in wind farm wake modeling

Reliable prediction of wind turbine wakes is essential for the optimal design and operation of wind farms. In order to achieve this, the parameter uncertainty of analytical wake model is investigated for the first time. Specifically, large eddy simulations (LES) of wind farms are carried out with different turbine yaw angles, based on SOWFA (Simulator fOr Wind Farm Applications) platform. The generated high-fidelity flow field data is used to infer the low-fidelity model’s parameters within the Bayesian uncertainty quantification framework. After model calibration, the posterior model check shows that the predicted mean velocity profile with the quantified uncertainty matches well with the high-fidelity CFD data. The prediction of other quantities, such as wind farm flow field and turbine power generation, is also carried out. The results show that the wake model with the model parameters specified by their posterior distributions can be seen as the stochastic extension of the original wake model. As most of the existing wake models are static, the resulting stochastic model shows a great advantage over the original model, as it can give not only the static wind farm properties but also their statistical distributions.

공급신뢰도 측면에서의 신재생에너지발전단지와 연계된 BESS의 운용 알고리즘 개발

This paper proposes a probabilistic reliability evaluation model and algorithm for the power system considering wind turbine generator (WTG) and battery energy storage system (BESS) in viewpoint of power system reliability. A large-scale wind turbine generator (WTG) can creates significant power fluctuations and should affect the stability, frequency control and then reliability of the power system. Therefore, wind power should be limited to supply the percentage of load. The output of WTG cannot be predicted accurately and so results in significant fluctuations in power supply balance. Therefore, it is difficult to control the power balance between supply and demand. However, it can be controlled by installing the BESS. The BESS may smooth the fluctuation of the WTG power output. This paper proposes reliability based alternative algorithm in order to simulate the effects of the interaction of multiple WTG and BESS newly. Additionally, this paper presents sample system studies that single BESS as well as multi-BESS are simulated by handwork very clearly. Futhermore, the reliability effects of BESS according to a couple of different BESS operation rules and conditions are demonstrated in sample system case study.

Design and simulation of wind turbine on rail coach for power generation

Energy resources in our modern fast paced techno world are fast depleting. Hence a renewable energy source is much required at the moment Wind energy is a renewable source of energy. today, the output power from wind turbines can be utilized in two ways, either by direct use of the mechanical shaft power (through a gear in gear ratio) or by letting the wind turbine power and electrical generator, and utilizing the generated power as electrical power. This paper brings a new possibility for the utilization of the wind generated power, for various electrical components inside a typical railway train through the batteries, charged by the wind energy harnessed by a wind turbine mounted at the top of the train coaches. This setup consists of duct, turbine, and generator. The setup is designed in such a way that it does not affect the performance of the train. Average velocity is estimated for the train and the suitable specification of generator is selected. The theoretical calculations of duct, turbine and pulley parameters are calculated and the whole setup is designed in CATIA, also by varying the inlet air velocity, the speed and torque of the turbine are calculated using CFX software. These parameters are used for calculating generator’s speed and torque and are validated by comparing with the theoretical design calculations. Future advancements are discussed, and a path for experimental verification is proposed.