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

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.

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SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

Alternative Energy and Ecology (ISJAEE) ◽

10.15518/isjaee.2018.22-24.028-050 ◽

2018 ◽

pp. 28-50

Author(s):

S. G. Ignatiev ◽

S. V. Kiseleva

Keyword(s):

Energy Storage ◽

Wind Speed ◽

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Energy Demand ◽

Diesel Generator ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

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

Wind Energy Science ◽

10.5194/wes-6-1427-2021 ◽

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.

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

10.5194/wes-2021-61 ◽

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.

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Monitoring and Modeling Roof-Level Wind Speed in a Changing City

Atmosphere ◽

10.3390/atmos11010087 ◽

2020 ◽

Vol 11 (1) ◽

pp. 87

Author(s):

Kathrin Baumann-Stanzer ◽

Sirma Stenzel ◽

Gabriele Rau ◽

Martin Piringer ◽

Felix Feichtinger ◽

...

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Wind Turbine ◽

Urban Areas ◽

Dispersion Model ◽

Flow Direction ◽

Energy Yield ◽

Wind Speeds ◽

Small Wind Turbine ◽

Roof Level

Results of an observational campaign and model study are presented demonstrating how the wind field at roof-level in the urban area of Vienna changed due to the construction of a new building nearby. The investigation was designed with a focus on the wind energy yield of a roof-mounted small wind turbine but the findings are also relevant for air dispersion applications. Wind speed profiles above roof top are simulated with the complex fluid dynamics (CFD) model MISKAM (Mikroskaliges Klima- und Ausbreitungsmodell, microscale climate and dispersion model). The comparison to mast measurements reveals that the model underestimates the wind speeds within the first few meters above the roof, but successfully reproduces wind conditions at 10 m above the roof top (corresponding to about 0.5 times the building height). Scenario simulations with different building configurations at the adjacent property result in an increase or decrease of wind speed above roof top depending on the flow direction at the upper boundary of the urban canopy layer (UCL). The maximum increase or decrease in wind speed caused by the alternations in building structure nearby is found to be in the order of 10%. For the energy yield of a roof-mounted small wind turbine at this site, wind speed changes of this magnitude are negligible due to the generally low prevailing wind speeds of about 3.5 m s−1. Nevertheless, wind speed changes of this order could be significant for wind energy yield in urban areas with higher mean wind speeds. This effect in any case needs to be considered in siting and conducting an urban meteorological monitoring network in order to ensure the homogeneity of observed time-series and may alter the emission and dispersion of pollutants or odor at roof level.

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ANALISA PERFORMA TURBIN ANGIN SUMBU HORISONTAL BERSUDU AIRFOIL MELALUI VARIASI JUMLAH SUDU

ROTOR ◽

10.19184/rotor.v11i2.9338 ◽

2018 ◽

Vol 11 (2) ◽

pp. 18

Author(s):

Wabang A Jhon ◽

Abanat D.J Jufra ◽

Hattu Edwin

Keyword(s):

Wind Speed ◽

Kinetic Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Mechanical Energy ◽

Coefficient Of Performance ◽

Research Activity ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind

Indonesia is an area that has the potential for sufficient wind resources to be utilized for kinetic energy into other energy such as mechanical energy and electrical energy through its generators (generators). The way to utilize wind kinetic energy into other energy is through a device called a wind turbine. Wind turbines have been around since ancient times, and are called airfoil angled wind turbines. This airfoil wind turbine is designed only for areas with average wind speeds above 6m / s. While in Indonesia not all regions have the same wind speed. In certain seasons, the average wind speed is below 6 m / s. This has become a major problem in regions that have average wind speeds below 6 m / s. Seeing this condition, there is a need for scientific research to obtain wind turbines that can be used in areas with average wind speeds below 5m / s. For this reason, the research I want to do is get a wind turbine that can be used as a power plant in areas that have wind speeds below 6m / s. This research was conducted on the basis of scientific theory in fluid mechanics regarding the sweeping area of wind turbines and the performance of variations in the number of blades in the wind. In addition, the research in several scientific journals was used as the basis of this research This research method is an experimental method, in the form of testing a wind turbine axis prototype horizontal and airfoil axis. The details of the research activity are the design and manufacture of laboratory scale horizontal airfoil axis turbines. Next, testing with a fan as a source of wind. The fan used has three variations of speed, all of which are used to determine the lowest average wind speed that can be applied. The results of the research are where wind turbines with the greatest torque and power and the Coefficient of Performance (CP) with the highest value will be used as a result to be applied to the community. Based on experimental data, it can be concluded that the greatest torque and power occur in turbines with 4 blades with details at speed 1, the largest torque and power are 0.201 Nm and 4.5 W; at speed 2, the biggest torque and power are 0.25 Nm and 7.21 W; at speed 3, the biggest torque and power are 0.28 Nm and 8.35 W Keywords: wind turbine, airfoil, nozzle, diffuser

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Measuring Sub-second Wind Velocity Changes for Agricultural Drift One Meter Above the Ground

Applied Engineering in Agriculture ◽

10.13031/aea.12264 ◽

2019 ◽

Vol 35 (5) ◽

pp. 697-704

Author(s):

Matthew W. Schramm ◽

H Mark Hanna ◽

Matt J. Darr ◽

Steven J. Hoff ◽

Brian L. Steward

Keyword(s):

Wind Speed ◽

Solar Radiation ◽

Wind Velocity ◽

Wind Direction ◽

Weather Conditions ◽

Spray Drift ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind ◽

Velocity Changes

Abstract. Agricultural spray drift is affected by many factors including current weather conditions, topography of the surrounding area, fluid properties at the nozzle, and the height at which the spray is released. During the late spring/summer spray seasons of 2014 and 2015, wind direction, speed, and solar radiation (2014 only) were measured at 10 Hz, 1 m above the ground to investigate conditions that are typically encountered by a droplet when released from a nozzle on an agricultural sprayer. Measurements of wind velocity as the wind passed from an upwind sensor to a downwind sensor were used to evaluate what conditions wind may be most likely to have a significant direction or speed change which affects droplet trajectory. For two individual datasets in which the average wind speed was 3.6 and 1.5 m/s (8.0 and 3.4 mi/h), there exists little linear correlation of wind speed or wind direction between an upwind and downwind anemometer separated by 30.5 m (100 ft). The highest observed correlation, resulting from a 12-s lag between the upwind and downwind datasets, was 0.29 when the average wind speed was 3.6 m/s (8.0 mi/h). Correlations greater than 0.1 were only found for wind speeds exceeding 3 m/s. Using this lag time, it was observed that the wind direction 30 s into the future had a 30% chance to be different by more than 20° from current conditions. A wind speed difference of more than 1 m/s (2.2 mi/h) from current conditions [mean wind speed was 3.6 m/s (8.0 mi/h)] was observed about 50% of the time. Analyzing 36 days of the 2014 and 2015 spray season wind velocity data showed that the most variability in wind direction occurred with wind speeds below 2 m/s (4.5 mi/h). Greater wind direction variability occurred in the mid-afternoon with higher solar radiation. Keywords: Sprayers, Spray drift, Spray droplets, Turbulence, Wind effects.

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

Volume 9A: Ocean Renewable Energy ◽

10.1115/omae2014-23621 ◽

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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Analysis of Performance of the Wind-Driven Pulverizing Aerator Based on Average Wind Speeds in the Conditions of Góreckie Lake

Energies ◽

10.3390/en14102796 ◽

2021 ◽

Vol 14 (10) ◽

pp. 2796

Author(s):

Andrzej Osuch ◽

Ewa Osuch ◽

Stanisław Podsiadłowski ◽

Piotr Rybacki

Keyword(s):

Mathematical Model ◽

Wind Speed ◽

Water Pump ◽

Average Wind Speed ◽

Flow Rates ◽

Wind Speeds ◽

Average Wind ◽

Flow Through ◽

Analysis Of Performance ◽

Research Period

In the introduction to this paper, the characteristics of Góreckie lake and the construction and operation of the wind-driven pulverizing aerator are presented. The purpose of this manuscript is to determine the efficiency of the pulverizing aerator unit in the windy conditions of Góreckie Lake. The efficiency of the pulverization aerator depends on the wind conditions at the lake. It was necessary to conduct thorough research to determine the efficiency of water flow through the pulverization segment (water pump). It was necessary to determine the rotational speed of the paddle wheel, which depended on the average wind speed. Throughout the research period, measurements of hourly average wind speed were carried out. It was possible to determine the efficiency of the machine by developing a dedicated mathematical model. The latest method was used in the research, consisting of determining the theoretical volumetric flow rates of water in the pulverizing aerator unit, based on average hourly wind speeds. Pulverization efficiency under the conditions of Góreckie Lake was determined based on 6600 average wind speeds for spring, summer and autumn, 2018. Based on the model, the theoretical efficiency of the machine was calculated, which, under the conditions of Góreckie Lake, amounted to 75,000 m3 per year.

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Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction

Weather and Forecasting ◽

10.1175/waf-d-17-0091.1 ◽

2017 ◽

Vol 32 (6) ◽

pp. 2217-2227 ◽

Cited By ~ 7

Author(s):

Siri Sofie Eide ◽

John Bjørnar Bremnes ◽

Ingelin Steinsland

Keyword(s):

Wind Speed ◽

Wind Direction ◽

Bayesian Model Averaging ◽

Weather Prediction ◽

Model Averaging ◽

Strong Wind ◽

Ensemble Forecasts ◽

Wind Speeds ◽

Low Wind Speeds ◽

The One

Abstract In this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one subject to forecasting is common for statistical calibration of deterministic forecasts. However, this practice is rarely seen for ensemble forecasts, probably because of a lack of methods. A Bayesian modeling approach (BMA) is adopted, and a flexible model class based on splines is introduced for the mean model. The spline model allows both wind speed and wind direction to be included nonlinearly. The proposed methodology is tested for forecasting hourly maximum 10-min wind speeds based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts at 204 locations in Norway for lead times from +12 to +108 h. An improvement in the continuous ranked probability score is seen for approximately 85% of the locations using the proposed method compared to standard BMA based on only wind speed forecasts. For moderate-to-strong wind the improvement is substantial, while for low wind speeds there is generally less or no improvement. On average, the improvement is 5%. The proposed methodology can be extended to include more NWP variables in the calibration and can also be applied to other variables.

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Design of Small Wind Turbine

Volume 1: Symposia, Parts A and B ◽

10.1115/fedsm2008-55326 ◽

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.

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