scholarly journals Wake redirection at higher axial induction

2021 ◽  
Vol 6 (2) ◽  
pp. 377-388
Author(s):  
Carlo Cossu
Keyword(s):  
Wind Farm ◽  
Offshore Wind ◽  
Negative Effects ◽  
Disk Model ◽  
Large Power ◽  
Control Approach ◽  
Yaw Control ◽  
Wake Interactions ◽  
Combined Control ◽  
Aligned Array

Abstract. The energy produced by wind plants can be increased by mitigating the negative effects of turbine–wake interactions. In this context, axial-induction control and wake redirection control, obtained by intentionally yawing or tilting the rotor axis away from the mean wind direction, have been the subject of extensive research but only very few investigations have considered their combined effect. In this study we compute power gains that are obtained by operating tilted and yawed rotors at higher axial induction by means of large-eddy simulations using the realistic native National Renewable Energy Laboratory (NREL) 5 MW actuator disk model implemented in the Simulator for On/Offshore Wind Farm Applications (SOWFA). We show that, for the considered two-row wind-aligned array of wind turbines, the power gains of approximately 5 % obtained by standard wake redirection at optimal tilt or yaw angles and reference axial induction can be more than tripled, to above 15 %, by operating the tilted or yawed turbines at higher axial induction. It is also shown that significant enhancements in the power gains are obtained even for moderate overinduction. These findings confirm the potential of overinductive wake redirection highlighted by previous investigations based on more simplified turbine models that neglected wake rotation effects. The results also complement previous research on dynamic overinductive yaw control by showing that it leads to large power gain enhancements also in the case where both the yaw and the overinduction controls are static, hopefully easing the rapid testing and implementation of this combined-control approach.

scholarly journals Comparing and validating intra-farm and farm-to-farm wakes across different mesoscale and high-resolution wake models

2021 ◽  
Author(s):  
Jana Fischereit ◽  
Kurt Schaldemose Hansen ◽  
Xiaoli Guo Larsén ◽  
Maarten Paul van der Laan ◽  
Pierre-Elouan Réthoré ◽  
...  
Keyword(s):  
High Resolution ◽  
Wind Energy ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wake Effect ◽  
Disk Model ◽  
Computational Costs ◽  
Rans Simulations ◽  
Wind Resource

Abstract. Numerical wind resource modelling across scales from mesoscale to turbine scale is of increasing interest due to the expansion of offshore wind energy. Offshore, wind farm wakes can last several tens kilometres downstream and thus affect the wind resources of a large area. So far, scale-specific models have been developed and it remains unclear, how well the different model types can represent intra-farm wakes, farm-to-farm wakes as well as the wake recovery behind a farm. Thus, in the present analysis the simulation of a set of wind farm models of different complexity, fidelity, scale and computational costs are compared among each other and with SCADA data. In particular, two mesoscale wind farm parameterizations implemented in the mesoscale Weather Research and Forecasting model (WRF), the Explicit Wake Parameterization (EWP) and the Wind Farm Parameterization (FIT), two different high-resolution RANS simulations using PyWakeEllipSys equipped with an actuator disk model, and three rapid engineering wake models from the PyWake suite are selected. The models are applied to the Nysted and Rødsand II wind farms, which are located in the Fehmarn Belt in the Baltic Sea. Based on the performed simulations, we can conclude that average intra-farm variability can be captured reasonable well with WRF+FIT using a resolution of 2 km, a typical resolution of mesoscale models for wind energy applications, while WRF+EWP underestimates wind speed deficits. However, both parameterizations can be used to estimate median wind resource reduction caused by an upstream farm. All considered engineering wake models from the PyWake suite simulate intra-farm wakes comparable to the high fidelity RANS simulations. However, they considerably underestimate the farm wake effect of an upstream farm although with different magnitudes. Overall, the higher computational costs of PyWakeEllipSys and WRF compared to PyWake pay off in terms of accuracy for situations when farm-to-farm wakes are important.

Analysis of a multi turbine offshore wind farm connected to a single large power converter operated with variable frequency

Energy ◽  
2011 ◽  
Vol 36 (5) ◽  
pp. 3272-3281 ◽  
Author(s):  
Mikel de Prada Gil ◽  
Oriol Gomis-Bellmunt ◽  
Andreas Sumper ◽  
Joan Bergas-Jané
Keyword(s):  
Wind Farm ◽  
Power Converter ◽  
Offshore Wind ◽  
Variable Frequency ◽  
Offshore Wind Farm ◽  
Large Power

scholarly journals Field Test of Wake Steering at an Offshore Wind Farm

2017 ◽  
Author(s):  
Paul Fleming ◽  
Jennifer Annoni ◽  
Jigar J. Shah ◽  
Linpeng Wang ◽  
Shreyas Ananthan ◽  
...  
Keyword(s):  
Field Test ◽  
Wind Farm ◽  
Offshore Wind ◽  
Engineering Model ◽  
Offshore Wind Farm ◽  
Steering Control ◽  
Dynamics Model ◽  
Yaw Control ◽  
Control Optimization ◽  
Smart Energy Management

Abstract. In this paper, a field test of wake steering control is presented. The field test is the result of a collaboration between the National Renewable Energy Laboratory (NREL) and Envision Energy, a smart energy management company and turbine manufacturer. In the campaign, an array of turbines within an operating commercial offshore wind farm in China have the normal yaw controller modified to implement wake steering according to a yaw control strategy. The strategy was designed using NREL wind farm models, including a computational fluid dynamics model, SOWFA, for understanding wake dynamics and an engineering model, FLORIS, for yaw control optimization. Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture, by amounts similar to those predicted from the models.

scholarly journals On the Robustness of Active Wake Control to Wind Turbine Downtime

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3152
Author(s):  
Stoyan Kanev
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Offshore Wind ◽  
Negative Effects ◽  
Collaborative Control ◽  
Potential Benefits ◽  
Production Increase ◽  
The Impact

Active wake control (AWC) is an operational strategy for wind farms that aims at reducing the negative effects of wakes behind wind turbines on the power production and mechanical loads at the wind turbines’ downstream. For a given wind direction, the strategy relies on collaborative control of the machines within each row of turbines that affect each other through their wakes. The vast amount of research performed during the last decade indicates that the potential upside of this technology on the annual energy production of a wind farm can be as high as a few percentage points. Although these predictions on the potential benefits are quite significant, they typically assume full availability of all turbines within a row operating under AWC. However, even though the availability of offshore wind turbines is nowadays quite high (as high as 95%, or even higher), the availability of a whole row of turbines is shown to be much lower (lower than 60% for a row of ten turbines). This paper studies the impact of turbine downtime on the power production increase from AWC, and concludes that the AWC is robust enough to be kept operational in the presence of turbines standing still.

scholarly journals An Improved Power Control Approach for Wind Turbine Fatigue Balancing in an Offshore Wind Farm

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1549 ◽  
Author(s):  
Rongyong Zhao ◽  
Daheng Dong ◽  
Cuiling Li ◽  
Steven Liu ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Power Control ◽  
Wind Turbines ◽  
Wind Farm ◽  
Automata Theory ◽  
Offshore Wind ◽  
Maintenance Cost ◽  
Offshore Wind Farm ◽  
Control Approach ◽  
Power Dispatch ◽  
Fatigue Loads

Increasing maintenance costs will hinder the expansion of the wind power industry in the coming decades. Training personnel, field maintenance, and frequent boat or helicopter visits to wind turbines (WTs) is becoming a large cost. One reason for this cost is the routine turbine inspection repair and other stochastic maintenance necessitated by increasingly unbalanced figure loads and unequal turbine fatigue distribution in large-scale offshore wind farms (OWFs). In order to solve the problems of unbalanced fatigue loads and unequal turbine fatigue distribution, thereby cutting the maintenance cost, this study analyzes the disadvantages of conventional turbine fatigue definitions. We propose an improved fatigue definition that simultaneously considers the mean wind speed, wind wake turbulence, and electric power generation. Further, based on timed automata theory, a power dispatch approach is proposed to balance the fatigue loads on turbines in a wind farm. A control topology is constructed to describe the logical states of the wind farm main controller (WFMC) in an offshore wind farm. With this novel power control approach, the WFMC can re-dispatch the reference power to the wind turbines according to their cumulative fatigue value and the real wind conditions around the individual turbines in every power dispatch time interval. A workflow is also designed for the control approach implementation. Finally, to validate this proposed approach, wind data from the Horns Rev offshore wind farm in Denmark are used for a numerical simulation. All the simulation results with 3D and 2D figures illustrate that this approach is feasible to balance the loads on an offshore wind farm. Some significant implications are that this novel approach can cut the maintenance cost and also prolong the service life of OWFs.

scholarly journals Field test of wake steering at an offshore wind farm

2017 ◽  
Vol 2 (1) ◽  
pp. 229-239 ◽  
Author(s):  
Paul Fleming ◽  
Jennifer Annoni ◽  
Jigar J. Shah ◽  
Linpeng Wang ◽  
Shreyas Ananthan ◽  
...  
Keyword(s):  
Field Test ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Steering Control ◽  
Dynamics Model ◽  
Yaw Control ◽  
Control Optimization ◽  
Model Flow ◽  
Smart Energy Management

Abstract. In this paper, a field test of wake-steering control is presented. The field test is the result of a collaboration between the National Renewable Energy Laboratory (NREL) and Envision Energy, a smart energy management company and turbine manufacturer. In the campaign, an array of turbines within an operating commercial offshore wind farm in China have the normal yaw controller modified to implement wake steering according to a yaw control strategy. The strategy was designed using NREL wind farm models, including a computational fluid dynamics model, Simulator fOr Wind Farm Applications (SOWFA), for understanding wake dynamics and an engineering model, FLOw Redirection and Induction in Steady State (FLORIS), for yaw control optimization. Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture, by amounts similar to those predicted from the models.

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