scholarly journals Evaluation of wind turbine power outputs with and without uncertainties in input wind speed and wind direction data

2020 ◽  
Vol 14 (15) ◽  
pp. 2801-2809 ◽  
Author(s):  
M. Zou ◽  
D. Fang ◽  
S.Z. Djokic ◽  
V. Di Giorgio ◽  
R. Langella ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Power Outputs

Design of Small Wind Turbine

2008 ◽  
Author(s):  
R. S. Amano ◽  
Ryan Malloy
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Pitch Angle ◽  
Bridge Circuit ◽  
Small Wind Turbine ◽  
Swash Plate ◽  
Wind Vane ◽  
Blade Pitch Angle

The project has been completed, and all of the aforementioned objectives have been achieved. An anemometer has been constructed to measure wind speed, and a wind vane has been built to sense wind direction. An LCD module has been acquired and has been programmed to display the wind speed and its direction. An H-Bridge circuit was used to drive a gear motor that rotated the nacelle toward the windward direction. Finally, the blade pitch angle was controlled by a swash plate mechanism and servo motors installed on the generator itself. A microcontroller has been programmed to optimally control the servo motors and gear motor based on input from the wind vane and anemometer sensors.

scholarly journals Numerical Simulation of the Aeroelastic Response of Wind Turbines in Typhoons Based on the Mesoscale WRF Model

2019 ◽  
Vol 12 (1) ◽  
pp. 34
Author(s):  
Long Wang ◽  
Cheng Chen ◽  
Tongguang Wang ◽  
Weibin Wang
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Flow Direction ◽  
Wrf Model ◽  
Normal Operation ◽  
Average Wind Speed ◽  
Aeroelastic Response ◽  
Response Characteristics ◽  
Wind Speeds

A new simulation method for the aeroelastic response of wind turbines under typhoons is proposed. The mesoscale Weather Research and Forecasting (WRF) model was used to simulate a typhoon’s average wind speed field. The measured power spectrum and inverse Fourier transform method were coupled to simulate the pulsating wind speed field. Based on the modal method and beam theory, the wind turbine model was constructed, and the GH-BLADED commercial software package was used to calculate the aerodynamic load and aeroelastic response. The proposed method was applied to assess aeroelastic response characteristics of a commercial 6 MW offshore wind turbine under different wind speeds and direction variation patterns for the case study of typhoon Hagupit (2008), with a maximal wind speed of 230 km/h. The simulation results show that the typhoon’s average wind speed field and turbulence characteristics simulated by the proposed method are in good agreement with the measured values: Their difference in the main flow direction is only 1.7%. The scope of the wind turbine blade in the typhoon is significantly larger than under normal wind, while that under normal operation is higher than that under shutdown, even at low wind speeds. In addition, an abrupt change in wind direction has a significant impact on wind turbine response characteristics. Under normal operation, a sharp variation of the wind direction by 90 degrees in 6 s increases the wind turbine (WT) vibration scope by 27.9% in comparison with the case of permanent wind direction. In particular, the maximum deflection of the wind tower tip in the incoming flow direction reaches 28.4 m, which significantly exceeds the design standard safety threshold.

scholarly journals Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance

2021 ◽  
Vol 6 (6) ◽  
pp. 1427-1453
Author(s):  
Eric Simley ◽  
Paul Fleming ◽  
Nicolas Girard ◽  
Lucas Alloin ◽  
Emma Godefroy ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Direction ◽  
Wind Farm ◽  
Poor Performance ◽  
Power Production ◽  
Wind Rose ◽  
Wind Speeds ◽  
Variability Model

Abstract. Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake-steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the 3-month experiment period, we estimate that wake steering reduced wake losses by 5.6 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.3 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6–8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8–12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake-steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6–8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the expected yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.

scholarly journals Results from a Wake Steering Experiment at a Commercial Wind Plant: Investigating the Wind Speed Dependence of Wake Steering Performance

2021 ◽  
Author(s):  
Eric Simley ◽  
Paul Fleming ◽  
Nicolas Girard ◽  
Lucas Alloin ◽  
Emma Godefroy ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Direction ◽  
Wind Farm ◽  
Poor Performance ◽  
Power Production ◽  
Wind Rose ◽  
Wind Speeds ◽  
Variability Model

Abstract. Wake steering is a wind farm control strategy in which upstream wind turbines are misaligned with the wind to redirect their wakes away from downstream turbines, thereby increasing the net wind plant power production and reducing fatigue loads generated by wake turbulence. In this paper, we present results from a wake steering experiment at a commercial wind plant involving two wind turbines spaced 3.7 rotor diameters apart. During the three-month experiment period, we estimate that wake steering reduced wake losses by 5.7 % for the wind direction sector investigated. After applying a long-term correction based on the site wind rose, the reduction in wake losses increases to 9.8 %. As a function of wind speed, we find large energy improvements near cut-in wind speed, where wake steering can prevent the downstream wind turbine from shutting down. Yet for wind speeds between 6–8 m/s, we observe little change in performance with wake steering. However, wake steering was found to improve energy production significantly for below-rated wind speeds from 8–12 m/s. By measuring the relationship between yaw misalignment and power production using a nacelle lidar, we attribute much of the improvement in wake steering performance at higher wind speeds to a significant reduction in the power loss of the upstream turbine as wind speed increases. Additionally, we find higher wind direction variability at lower wind speeds, which contributes to poor performance in the 6–8 m/s wind speed bin because of slow yaw controller dynamics. Further, we compare the measured performance of wake steering to predictions using the FLORIS (FLOw Redirection and Induction in Steady State) wind farm control tool coupled with a wind direction variability model. Although the achieved yaw offsets at the upstream wind turbine fall short of the intended yaw offsets, we find that they are predicted well by the wind direction variability model. When incorporating the predicted achieved yaw offsets, estimates of the energy improvement from wake steering using FLORIS closely match the experimental results.

scholarly journals Wind turbine wake measurements with automatically adjusting scanning trajectories in a multi-Doppler lidar setup

2018 ◽  
Vol 11 (6) ◽  
pp. 3801-3814 ◽  
Author(s):  
Norman Wildmann ◽  
Nikola Vasiljevic ◽  
Thomas Gerz
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Sonic Anemometer ◽  
Prevailing Wind Direction ◽  
Wide Range ◽  
Novel Method ◽  
Approach Velocity ◽  
German Aerospace ◽  
First Time

Abstract. In the context of the Perdigão 2017 experiment, the German Aerospace Center (DLR) deployed three long-range scanning Doppler lidars with the dedicated purpose of investigating the wake of a single wind turbine at the experimental site. A novel method was tested for the first time to investigate wake properties with ground-based lidars over a wide range of wind directions. For this method, the three lidars, which were space- and time-synchronized using the WindScanner software, were programmed to measure with crossing beams at individual points up to 10 rotor diameters downstream of the wind turbine. Every half hour, the measurement points were adapted to the current wind direction to obtain a high availability of wake measurements in changing wind conditions. The linearly independent radial velocities where the lidar beams intersect allow the calculation of the wind vector at those points. Two approaches to estimating the prevailing wind direction were tested throughout the campaign. In the first approach, velocity azimuth display (VAD) scans of one of the lidars were used to calculate a 5 min average of wind speed and wind direction every half hour, whereas later in the experiment 5 min averages of sonic anemometer measurements of a meteorological mast close to the wind turbine became available in real time and were used for the scanning adjustment. Results of wind speed deficit measurements are presented for two measurement days with varying northwesterly winds, and it is evaluated how well the lidar beam intersection points match the actual wake location. The new method allowed wake measurements to be obtained over the whole measurement period, whereas a static scanning setup would only have captured short periods of wake occurrences.

scholarly journals Wind Turbine Wake Measurements with Automatically Adjusting Scanning Trajectories in a Multi-Doppler Lidar Setup

2018 ◽  
Author(s):  
Norman Wildmann ◽  
Nikola Vasiljevic ◽  
Thomas Gerz
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Sonic Anemometer ◽  
Prevailing Wind Direction ◽  
Wide Range ◽  
Engineering Models ◽  
Novel Method ◽  
German Aerospace ◽  
Turbine Wake

Abstract. In the context of the Perdigão 2017 experiment, the German Aerospace Center (DLR) deployed three long-range scanning Doppler lidars with the dedicated purpose of investigating the wake of a single wind turbine at the experimental site. A novel method was established to investigate wake properties with ground-based lidars over a wide range of wind directions. For this method, the three lidars, which were space- and time-synchronized using the WindScanner software, were programmed to measure with crossing beams at individual points up to ten rotor diameters downstream the wind turbine. Every half hour, the measurement points were adapted to the current wind direction to obtain a high availability of wake measurements in changing wind conditions. The linearly independent radial velocities where the lidar beams intersect allow the calculation of the wind vector at those points. Two approaches to estimate the prevailing wind direction were tested throughout the campaign. In the first approach, VAD scans of one of the lidars were used to calculate a five-minute average of wind speed and wind direction every half hour, whereas later in the experiment, five-minute averages of sonic anemometer measurements of a meteorological mast close to the wind turbine became available in real-time and were used for the scanning adjustment. Results of wind speed deficit measurements are presented for two measurement days with varying westerly winds and it is evaluated how well the lidar beam intersection points match the actual wake location. The new method allowed to obtain wake measurements over the whole measurement period, whereas a static scanning setup would only have captured short periods of wake occurrences. The analysed cases reveal that state-of-the-art engineering models for wakes underestimate the actual wind speed deficit.

Wind Direction Characteristics of a Vertical Axis Wind Turbine Using the Mechanism of a Bird’s Wing With a Wind Collector

2011 ◽  
Author(s):  
Yoshiaki Tanzawa ◽  
Takao Sato ◽  
Takumi Hashizume
Keyword(s):  
Computer Simulation ◽  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Direction ◽  
Vertical Axis ◽  
Vertical Axis Wind Turbine ◽  
Speed Distribution ◽  
Wind Speed Distribution ◽  
Savonius Wind Turbine

This paper describes the wind direction characteristics of the wind collector used for our 8th model of the vertical axis wind turbine using the mechanism of a bird’s wing. The 8th model is divided into two sections top and bottom. Each section looks like a Savonius wind turbine. The blade is divided into seven rows of plates. Each 0.18mm stainless plate has only one side attached to the frame. Wind from the outside enlarges the space between the blades, and passes through. However, wind from the inside closes the space. In the wind collector, four wind collection boards are located every 90 degrees around this wind turbine. In an earlier paper, it was confirmed that these collection boards collected 1.6 times the wind and resulted in twice the output. In this paper, the variations in the wind collector characteristics due to the wind direction are clarified experimentally. A wind tunnel experiment using six different wind directions shows that the output increases for four wind directions and decreases for one wind direction. Additionally, the computer simulation confirms the wind direction and the wind speed distribution around the wind turbine when the wind collection boards are in place.

Long-Term Extreme Response Analysis for a Fixed Offshore Wind Turbine Considering Blade-Pitch-Actuator Fault and Normal Transient Events

2014 ◽  
Author(s):  
Qinyuan Li ◽  
Zhen Gao ◽  
Torgeir Moan
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Direction ◽  
Normal Operation ◽  
Offshore Wind Turbine ◽  
Bending Moments ◽  
Start Up ◽  
Extreme Response ◽  
Transient Events

In this paper, the 50-year long-term 1-hour extreme responses of a fixed jacket-type offshore wind turbine with consideration of one-blade-pitch-actuator-stuck fault and the effect of normal transient events such as normal shut-down and start-up process is studied. The long-term extreme results are found based on each short-term extreme response distributions at different environmental conditions. Structure responses such as tower and jacket bottom shear and bending moments as well as blade root bending moments will be focused in this paper. To study the long-term effect of the fault and transient events, the service life of a wind turbine is divided into normal part, faulted part, and transient part. Normal part includes both normal operation and parking of the wind turbine at different wind speed range without any faults. Faulted part includes the parked and emergency shut-down condition of the wind turbine under the fault assuming that the faults are detected soon after they occur but require a longer time before fully repaired. Transient part includes the start-up and shut-down process during the normal operation when wind speed is beyond operation range. The contribution of each part to the long-term extreme response distribution is calculated by weighting factors based on the probability of occurrence of each part. From the results, it is found that in general, the blade-pitch-actuator-stuck fault and the normal transient events generally increase the extreme responses of the wind turbine. The jacket wind turbine is more affected compared to its land based counterpart. In this study since the wind direction is aligned with wind turbine, it is found that the fault primarily increases the tower bottom shear force perpendicular to the wind direction and the bending moments with the axis parallel to the wind as well as the torsional moment, while normal transient events, especially the start-up process at cut-out speed, causes a much greater increase compared to the fault. It contribute mostly to the shear forces parallel and bending moment with axis perpendicular to the wind direction. The azimuth of the blades is found to be very important for blade responses during start-up process especially at higher wind speed.

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