scholarly journals Analytical model for the power–yaw sensitivity of wind turbines operating in full wake

2020 ◽  
Vol 5 (1) ◽  
pp. 427-437 ◽  
Author(s):  
Jaime Liew ◽  
Albert M. Urbán ◽  
Søren Juhl Andersen
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Power Production ◽  
Wake Flow ◽  
High Fidelity ◽  
Combined Effects ◽  
Wind Farm Optimization ◽  
Computational Fluid Dynamics Simulations ◽  
Dynamics Simulations ◽  
Blade Element

Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increases for turbines operating in the wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated, with a focus on the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the wake inflow in order to determine a power–yaw loss exponent. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium- and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation in the incoming wind field, due to the presence of wakes, plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power–yaw loss exponent can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30∘. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the combined effects of wakes and yaw misalignment as well as the uncertainty on power output.

scholarly journals Analytical model for the power-yaw sensitivity of wind turbines operating in full wake

2019 ◽  
Author(s):  
Jaime Liew ◽  
Albert M. Urbán ◽  
Søren Juhl Andersen
Keyword(s):  
Wind Turbines ◽  
Wind Field ◽  
Wind Farm ◽  
Power Production ◽  
Loss Coefficient ◽  
Wake Flow ◽  
Wind Farm Optimization ◽  
Wake Effects ◽  
Computational Fluid Dynamics Simulations ◽  
Dynamics Simulations

Abstract. Wind turbines are designed to align themselves with the incoming wind direction. However, turbines often experience unintentional yaw misalignment, which can significantly reduce the power production. The unintentional yaw misalignment increase for turbines operating in wake of upstream turbines. Here, the combined effects of wakes and yaw misalignment are investigated with the resulting reduction in power production. A model is developed, which considers the trajectory of each turbine blade element as it passes through the waked wind field in order to determine a power-yaw loss coefficient. The simple model is verified using the HAWC2 aeroelastic code, where wake flow fields have been generated using both medium and high-fidelity computational fluid dynamics simulations. It is demonstrated that the spatial variation of the incoming wind field, due to the presence of wake(s), plays a significant role in the power loss due to yaw misalignment. Results show that disregarding these effects on the power-yaw loss coefficient can yield a 3.5 % overestimation in the power production of a turbine misaligned by 30°. The presented analysis and model is relevant to low-fidelity wind farm optimization tools, which aim to capture the effects of wake effects and yaw misalignment as well as uncertainty on power output.

scholarly journals Time-Averaged Wind Turbine Wake Flow Field Prediction Using Autoencoder Convolutional Neural Networks

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 41
Author(s):  
Zexia Zhang ◽  
Christian Santoni ◽  
Thomas Herges ◽  
Fotis Sotiropoulos ◽  
Ali Khosronejad
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Power Production ◽  
Velocity Fields ◽  
Large Eddy Simulations ◽  
Wake Flow ◽  
Surface Model ◽  
Flow Conditions ◽  
Large Eddy ◽  
Turbine Wake

A convolutional neural network (CNN) autoencoder model has been developed to generate 3D realizations of time-averaged velocity in the wake of the wind turbines at the Sandia National Laboratories Scaled Wind Farm Technology (SWiFT) facility. Large-eddy simulations (LES) of the SWiFT site are conducted using an actuator surface model to simulate the turbine structures to produce training and validation datasets of the CNN. The simulations are validated using the SpinnerLidar measurements of turbine wakes at the SWiFT site and the instantaneous and time-averaged velocity fields from the training LES are used to train the CNN. The trained CNN is then applied to predict 3D realizations of time-averaged velocity in the wake of the SWiFT turbines under flow conditions different than those for which the CNN was trained. LES results for the validation cases are used to evaluate the performance of the CNN predictions. Comparing the validation LES results and CNN predictions, we show that the developed CNN autoencoder model holds great potential for predicting time-averaged flow fields and the power production of wind turbines while being several orders of magnitude computationally more efficient than LES.

scholarly journals A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 8 ◽  
Author(s):  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Production ◽  
Test Case ◽  
Before And After ◽  
Input Variables ◽  
The Impact

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.

Design Analysis of Critical Concepts Influence Wind Farm Production and Efficiency

2018 ◽  
Vol 40 ◽  
pp. 136-150
Author(s):  
Naima Charhouni ◽  
Mohammed Sallaou ◽  
Khalifa Mansouri
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Production Efficiency ◽  
Wind Farms ◽  
Power Production ◽  
Separation Distance ◽  
Design Analysis ◽  
Offshore Wind ◽  
Farm Production ◽  
Wind Farm Design

Wind farm deficiency caused by wake turbine interactions has received an important attention by scientific researchers in recent years. However the quality of power production is strongly depends on wind turbines location from others. In this regard, this paper proposes a comprehensive design analysis of crucial concepts that aid to plan for an efficient wind farm design. Indeed, the wake modeling problem is addressed in this analysis by comparing three models with available measured data gotten from literature. A configuration of wind turbines placement within the offshore wind farm as a function of separation distance is investigated in this study considering four wind farms layout. In addition to these elements, four rotor diameters size are evaluated as critical concept for wind turbine selection and production .The results obtained demonstrate that it is complicated to make a balance between three conflicted objectives related to the power production, efficiency and surface land area required for wind farm as a function of these crucial concepts.

Effect of Flow Inclination on Wind Turbine Performance

2012 ◽  
Vol 134 (12) ◽  
Author(s):  
Christina Tsalicoglou ◽  
Sarah Barber ◽  
Ndaona Chokani ◽  
Reza S. Abhari
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Complex Terrain ◽  
Wake Flow ◽  
Test Facility ◽  
Power Coefficient ◽  
Incoming Flow ◽  
Turbine Performance ◽  
The Impact ◽  
Blade Element

This work examines the effect of flow inclination on the performance of a stand-alone wind turbine and of wind turbines operating in the wakes of upstream turbines. The experimental portion of this work, which includes performance and flowfield measurements, is conducted in the ETH dynamically-scaled wind turbine test facility, with a wind turbine model that can be inclined relative to the incoming flow. The performance of the wind turbine is measured with an in-line torquemeter, and a 5-hole steady-state probe is used to detail the inflow and wake flow of the turbine. Measurements show that over a range of tip-speed ratios of 4–7.5, the power coefficient of a wind turbine with an incoming flow of 15 deg inclination decreases on average by 7% relative to the power coefficient of a wind turbine with a noninclined incoming flow. Flowfield measurements show that the wake of a turbine with an inclined incoming flow is deflected; the deflection angle is approximately 6 deg for an incoming flow with 15 deg inclination. The measured wake profiles are used as inflow profiles for a blade element momentum code in order to quantify the impact of flow inclination on the performance of downstream wind turbines. In comparison to the case without inclination in the incoming flow, the combined power output of two aligned turbines with incoming inclined flow decreases by 1%, showing that flow inclination in complex terrain does not significantly reduce the energy production.

Wind Farm Micro-Siting Optimization and Benefits Analysis

2014 ◽  
Vol 1055 ◽  
pp. 389-393
Author(s):  
Ze Jia Hua ◽  
Yan Zhang Gu ◽  
Chen Xuan Hou
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Power Production ◽  
Economic Benefits ◽  
Stable Operation ◽  
Technical Parameters

This paper puts forward a creative turbine micro-siting scheme breaking the 3D-5D rule, and calculates wake losses, power production and its economic benefits in traditional wind farm micro-siting scheme and creative wind farm micro-siting scheme by evaluating software WEPAS and MWVE. Results show that the micro-siting scheme breaking 3D-5D is more feasible and effective. It not only ensures the safe and stable operation of the wind turbines and technical parameters, but also the power production and the initial investment have been optimized.

A Study of Power Production and Noise Generation of a Small Wind Turbine for an Urban Environment

2017 ◽  
Author(s):  
Andrew Hays ◽  
Kenneth Van Treuren
Keyword(s):  
Urban Environment ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Power Production ◽  
Small Scale ◽  
Momentum Theory ◽  
Small Wind Turbines ◽  
Noise Measurements ◽  
Utility Scale ◽  
Blade Element

Wind energy has had a major impact on the generation of renewable energy. While most research and development focuses on large, utility-scale wind turbines, a new application is in the field of small wind turbines in the urban environment. A major design challenge for these urban wind turbines is the noise generated during operation. This study examines the power production and the noise generated by two small-scale wind turbines tested in a small wind tunnel. Both rotors were designed using the Blade-Element Momentum Theory and either the NREL S823 or the Eppler 216 airfoils. Point noise measurements were taken using a 1/4” microphone at three locations downstream of the turbine: 16% of the diameter (two chord lengths), 50% of the diameter, and 75% of the diameter. At each horizontal location downstream of the turbine, a vertical traverse was performed to analyze the sound pressure level from the tip of the turbine blades down to the hub. The rotor designed with the Eppler 216 airfoil showed a 9% increase in power production and decrease of up to 7 dB(A).

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.

A Study of Power Production and Noise Generation of a Small Wind Turbine for an Urban Environment

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Andrew Hays ◽  
Kenneth W. Van Treuren
Keyword(s):  
Urban Environment ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Power Production ◽  
Small Scale ◽  
Momentum Theory ◽  
Small Wind Turbines ◽  
Noise Measurements ◽  
Utility Scale ◽  
Blade Element

Wind energy has had a major impact on the generation of renewable energy. While most research and development focuses on large, utility-scale wind turbines, a new application is in the field of small wind turbines for the urban environment. A major design challenge for urban wind turbines is the noise generated during operation. This study examines the power production and the noise generated by two small-scale wind turbines tested in a small wind tunnel. Both rotors were designed using the blade-element momentum theory using either the NREL S823 or the Eppler 216 airfoils. Point noise measurements were taken using a microphone at three locations downstream of the turbine: 16% of the diameter (two chord lengths), 50% of the diameter, and 75% of the diameter. At each location downstream of the turbine, a vertical traverse was performed to analyze the sound pressure level (SPL) from the tip of the turbine blades down to the hub. The rotor designed with the Eppler 216 airfoil showed a 9% increase in power production and decrease of up to 7 dB(A).

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