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 ◽  
...  

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.

2021 ◽  
Author(s):  
Eric Simley ◽  
Paul Fleming ◽  
Nicolas Girard ◽  
Lucas Alloin ◽  
Emma Godefroy ◽  
...  

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.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7740
Author(s):  
Waldemar Kuczyński ◽  
Katarzyna Wolniewicz ◽  
Henryk Charun

The aim of the current paper is to present an approach to a wind turbine selection based on an annual wind measurements. The proposed approach led to a choice of an optimal device for the given wind conditions. The research was conducted for two potential wind farm locations, situated on the north of Poland. The wind measurements pointed out a suitability of the considered localizations for a wind farm development. Six types of wind turbines were investigated in each localization. The power of the wind turbines were in the range of 2.0 to 2.5 MW and with a medium size of the rotor being in the range of 82 to 100 m. The purpose of the research was to indicate a wind turbine with the lowest sensitivity to the variation of wind speed and simultaneously being most effective energetically. The Weibull density distribution was used in the analyses for three values of a shape coefficients k. The energy efficiency of the considered turbines were also assessed. In terms of the hourly distribution of the particular wind speeds, the most effective wind turbines were those with a nominal power of 2 MW, whereas the least effective were those with the nominal power of 2.3–2.5 MW. The novelty of the proposed approach is to analyze the productivity for many types of wind turbines in order to select the one which is the most effective energy producer. The analyses conducted in the paper allowed to indicate a wind turbine which generates the highest amount of energy independently on the wind speed variation.


1984 ◽  
Vol 106 (3) ◽  
pp. 347-350 ◽  
Author(s):  
D. E. Cromack ◽  
Debbie Oscar

The optimized design of a wind turbine depends on numerous parameters involving the entire machine (rotor, generator, etc.) and on the intended operating environment as described by the wind characteristics as well as on the load or application. This paper presents the design optimization process, identifies and discusses the influence of the various parameters, and then reviews the procedure by looking at two examples. The results of this process emphasize the relative importance of the design on rated wind speed, rotor rpm, generator size, and rotor blade characteristics. These results in general show that wind turbines have been designed for excessively high-rated wind speeds and generator capacities, except for those machines intended for wind farm applications and sites with particularly high winds. Machines designed for residential use should be sized to closely match the expected load and should be rated at a wind speed close to that value where the maximum energy contribution occurs. This wind speed is much lower than the rated wind speed for most currently available machines particularly for regions of relatively low annual mean wind speeds. Simplicity of design leads to a lower cost system, lower maintenance, and operating costs and greater reliability. It is this simply designed and optimized wind turbine that will have lasting success in the commercial market place.


2019 ◽  
Author(s):  
Miguel Sanchez Gomez ◽  
Julie K. Lundquist

Abstract. Numerous studies have shown that atmospheric conditions affect wind turbine performance, however, some findings have exposed conflicting results for different locations and diverse analysis methodologies. In this study, we explore how the change in wind direction with height (direction wind shear), a site-differing factor between conflicting studies, affects wind turbine performance. We utilized lidar and turbine data collected from the 2013 Crop Wind Energy eXperiment (CWEX) project between June and September in a wind farm in north-central Iowa. Directional wind shear was found to follow a diurnal cycle and to monotonically decrease with increasing wind speeds. Using different thresholds to distinguish between high- and low-directional wind shear scenarios, we found that larger thresholds evidence statistically-significant effects on turbine power production for lower wind speeds. We further analyzed a threshold of 0.225 deg m−1 and found turbine underperformance in the order of 10 % for wind speed regimes below 8 m s−1. Considering a time period of ramping electricity demand (05:30–09:00 LT) exposed the fact that large direction shear occurs during this time and is undermining turbine performance by more than 10 %. A predominance of clockwise direction shear (wind veering) cases compared to counterclockwise (wind backing) was also observed throughout the campaign. Moreover, large veering was found to have greater detrimental effects on turbine performance compared to small backing values. This study shows that changes in wind direction with height should be considered when analyzing turbine performance, however, future work on segregating speed and direction shear should be pursued to quantify the effects of only one factor on turbine power production.


2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Andrea Lombardi ◽  
Ludovico Terzi

The financial sustainability and the profitability of wind farms strongly depend on the efficiency of the conversion of wind kinetic energy. This motivates further research about the improvement of wind turbine power curve. If the site is characterized by a considerable occurrence of very high wind speeds, it can become particularly profitable to update the power curve management. This is commonly done by raising the cut-out velocity and the high wind speed cut-in regulating the hysteresis logic. Doing this, on one side, the wind turbine possibly undergoes strong vibration and loads. On the other side, the energy improvement is almost certain and the point is quantifying precisely its magnitude. In this work, the test case of an onshore wind farm in Italy is studied, featuring 17 2.3 MW wind turbines. Through the analysis of supervisory control and data acquisition (SCADA) data, the energy improvement from the extension of the power curve in the high wind speed region is simulated and measured. This could be useful for wind farm owners evaluating the realistic profitability of the installation of the power curve upgrade on their wind turbines. Furthermore, the present work is useful for the analysis of wind turbine behavior under extremely stressing load conditions.


2015 ◽  
Vol 137 (5) ◽  
Author(s):  
B. Subramanian ◽  
N. Chokani ◽  
R. S. Abhari

The aerodynamic characteristics of wakes in complex terrain have a profound impact on the energy yield of wind farms and on the fatigue loads on wind turbines in the wind farm. In order to detail the spatial variations of the wind speed, wind direction, and turbulent kinetic energy (TKE) in the near-wake, comprehensive drone-based measurements at a multi-megawatt (MW) wind turbine that is located in complex terrain have been conducted. A short-time Fourier transform (STFT)-based analysis method is used to derive time-localized TKE along the drone's trajectory. In upstream and in the near-wake, the vertical profiles of wind speed, wind direction, and TKE are detailed. There is an increase in the TKE from upstream to downstream of the wind turbine, and whereas, the characteristic microscale length scales increase with increasing height above the ground upstream of the turbine, in the near-wake the microscale lengths are of constant, smaller magnitude. The first-ever measurements of the pressure field across a multi-MW wind turbines rotor plane and of the tip vortices in the near-wake are also reported. It is shown that the pitch between subsequent tip vortices, which are shed from the wind turbines blades, increases in the near-wake as the wake evolves. These details of the near-wake can have an important effect on the subsequent evolution of the wake and must be incorporated into the three-dimensional (3D) field wake models that are currently under intensive development.


Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva

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.


2018 ◽  
Vol 64 ◽  
pp. 06010
Author(s):  
Bachhal Amrender Singh ◽  
Vogstad Klaus ◽  
Lal Kolhe Mohan ◽  
Chougule Abhijit ◽  
Beyer Hans George

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.


Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 8 ◽  
Author(s):  
Davide Astolfi

Pitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production.


2019 ◽  
Vol 12 (1) ◽  
pp. 34
Author(s):  
Long Wang ◽  
Cheng Chen ◽  
Tongguang Wang ◽  
Weibin Wang

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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