scholarly journals FLOWSTAR-Energy: a high resolution wind farm wake model

2016 ◽  
Author(s):  
Amy Stidworthy ◽  
David Carruthers
Keyword(s):  
Boundary Layer ◽  
Wind Turbine ◽  
Complex Terrain ◽  
Wind Farm ◽  
Wind Farms ◽  
Measured Data ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wake Model ◽  
Turbine Wake

Abstract. A new model, FLOWSTAR-Energy, has been developed for the practical calculation of wind farm energy production. It includes a semi-analytic model for airflow over complex surfaces (FLOWSTAR) and a wind turbine wake model that simulates wake-wake interaction by exploiting some similarities between the decay of a wind turbine wake and the dispersion of plume of passive gas emitted from an elevated source. Additional turbulence due to the wind shear at the wake edge is included and the assumption is made that wind turbines are only affected by wakes from upstream wind turbines. The model takes account of the structure of the atmospheric boundary layer, which means that the effect of atmospheric stability is included. A marine boundary layer scheme is also included to enable offshore as well as onshore sites to be modelled. FLOWSTAR-Energy has been used to model three different wind farms and the predicted energy output compared with measured data. Maps of wind speed and turbulence have also been calculated for two of the wind farms. The Tjaæreborg wind farm is an onshore site consisting of a single 2 MW wind turbine, the NoordZee offshore wind farm consists of 36 V90 VESTAS 3 MW turbines and the Nysted offshore wind farm consists of 72 Bonus 2.3 MW turbines. The NoordZee and Nysted measurement datasets include stability distribution data, which was included in the modelling. Of the two offshore wind farm datasets, the Noordzee dataset focuses on a single 5-degree wind direction sector and therefore only represents a limited number of measurements (1,284); whereas the Nysted dataset captures data for seven 5-degree wind direction sectors and represents a larger number of measurements (84,363). The best agreement between modelled and measured data was obtained with the Nysted dataset, with high correlation (0.98 or above) and low normalised mean square error (0.007 or below) for all three flow cases. The results from Tjæreborg show that the model replicates the Gaussian shape of the wake deficit two turbine diameters downstream of the turbine, but the lack of stability information in this dataset makes it difficult to draw conclusions about model performance. One of the key strengths of FLOWSTAR-Energy is its ability to model the effects of complex terrain on the airflow. However, although the airflow model has been previously compared extensively with flow data, it has so far not been used in detail to predict energy yields from wind farms in complex terrain. This will be the subject of a further validation study for FLOWSTAR-Energy.

scholarly journals Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

2018 ◽  
Author(s):  
Thomas Duc ◽  
Olivier Coupiac ◽  
Nicolas Girard ◽  
Gregor Giebel ◽  
Tuhfe Göçmen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Decay Constant ◽  
Wind Farms ◽  
Power Production ◽  
Original Model ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Onshore Wind ◽  
Wake Model

Abstract. In this paper, a new calculation procedure to improve the accuracy of the Jensen wake model for operating wind farms is proposed. In this procedure the wake decay constant is updated locally at each wind turbine based on the turbulence intensity measurement provided by the nacelle anemometer. This procedure was tested against experimental data at onshore wind farm La Sole du Moulin Vieux (SMV) in France and the offshore wind farm Horns Rev-I in Denmark. Results indicate that the wake deficit at each wind turbine is described more accurately than when using the original model, reducing the error from 15–20 % to approximately 5 %. Furthermore, this new model properly calibrated for the SMV wind farm is then used for coordinated control purposes. Assuming an axial induction control strategy, and following a model predictive approach, new power settings leading to an increased overall power production of the farm are derived. Power gains found are in the order of 2.5 % for a two wind turbine case with close spacing and 1 to 1.5 % for a row of five wind turbines with a larger spacing. Finally, the uncertainty of the updated Jensen model is quantified considering the model inputs. When checked against the predicted power gain, the uncertainty of the model estimations is seen to be excessive, reaching approximately 4 %, which indicates the difficulty of field observations for such a gain. Nevertheless, the optimized settings are to be implemented during a field test campaign at SMV wind farm in scope of the national project SMARTEOLE.

scholarly journals Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

2019 ◽  
Vol 4 (2) ◽  
pp. 287-302 ◽  
Author(s):  
Thomas Duc ◽  
Olivier Coupiac ◽  
Nicolas Girard ◽  
Gregor Giebel ◽  
Tuhfe Göçmen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Decay Constant ◽  
Wind Farms ◽  
Power Production ◽  
Original Model ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Onshore Wind ◽  
Wake Model

Abstract. In this paper, a new calculation procedure to improve the accuracy of the Jensen wake model for operating wind farms is proposed. In this procedure, the wake decay constant is updated locally at each wind turbine based on the turbulence intensity measurement provided by the nacelle anemometer. This procedure was tested against experimental data at the Sole du Moulin Vieux (SMV) onshore wind farm in France and the Horns Rev-I offshore wind farm in Denmark. Results indicate that the wake deficit at each wind turbine is described more accurately than when using the original model, reducing the error from 15 % to 20 % to approximately 5 %. Furthermore, this new model properly calibrated for the SMV wind farm is then used for coordinated control purposes. Assuming an axial induction control strategy, and following a model predictive approach, new power settings leading to an increased overall power production of the farm are derived. Power gains found are on the order of 2.5 % for a two-wind-turbine case with close spacing and 1 % to 1.5 % for a row of five wind turbines with a larger spacing. Finally, the uncertainty of the updated Jensen model is quantified considering the model inputs. When checked against the predicted power gain, the uncertainty of the model estimations is seen to be excessive, reaching approximately 4 %, which indicates the difficulty of field observations for such a gain. Nevertheless, the optimized settings are to be implemented during a field test campaign at SMV wind farm in the scope of the national project SMARTEOLE.

Performance Analysis of Offshore Mono-Pile Wind Turbine Co-Located With Floating Photovoltaic Systems in Shark Bay, Australia

2021 ◽  
Author(s):  
Morteza Bahadori ◽  
Hassan Ghassemi
Keyword(s):  
Wind Turbine ◽  
Hybrid System ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Shark Bay

Abstract In recent years, as more offshore wind farms have been constructed, the possibility of integrating various offshore renewable technologies is increased. Using offshore wind and solar power resources as a hybrid system provides several advantages including optimized marine space utilization, reduced maintenance and operation costs, and relieving wind variability on output power. In this research, both offshore wind and solar resources are analyzed based on accurate data through a case study in Shark Bay (Australia), where bathymetric information confirms using offshore bottom-fixed wind turbine regarding the depth of water. Also, the power production of the hybrid system of co-located bottom-fixed wind turbine and floating photovoltaic are investigated with the technical characteristics of commercial mono-pile wind turbine and photovoltaic panels. Despite the offshore wind, the solar energy output has negligible variation across the case study area, therefore using the solar platform in deep water is not an efficient option. It is demonstrated that the floating solar has a power production rate nearly six times more than a typical offshore wind farm with the same occupied area. Also, output energy and surface power density of the hybrid offshore windsolar system are improved significantly compared to a standalone offshore wind farm. The benefits of offshore wind and solar synergies augment the efficiency of current offshore wind farms throughout the world.

scholarly journals Optimal Power Dispatch of an Offshore Wind Farm under Generator Fault

2019 ◽  
Vol 9 (6) ◽  
pp. 1184 ◽  
Author(s):  
Kuichao Ma ◽  
Jiangsheng Zhu ◽  
Mohsen Soltani ◽  
Amin Hajizadeh ◽  
Zhe Chen
Keyword(s):  
Power Generation ◽  
Wind Turbine ◽  
Power Loss ◽  
Wind Farm ◽  
Wind Farms ◽  
Pso Algorithm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Optimal Power ◽  
Power Dispatch

For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimize the active power dispatch of wind farms under generator cooling system faults. The optimization objectives include avoiding the further deterioration of the generator fault, reducing unnecessary power loss of the faulty wind turbine, tracking the power demand from the Transmission System Operator (TSO), and reducing the power fluctuation caused by the PSO algorithm. The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can improve the power generation capacity of the wind farm and achieve an efficient trade-off between power generation and fault protection.

scholarly journals Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar

2006 ◽  
Vol 23 (7) ◽  
pp. 888-901 ◽  
Author(s):  
R. J. Barthelmie ◽  
G. C. Larsen ◽  
S. T. Frandsen ◽  
L. Folkerts ◽  
K. Rados ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Offshore Wind ◽  
Superior Performance ◽  
Offshore Wind Turbine ◽  
Wide Range ◽  
Wake Model ◽  
Method Of Evaluation ◽  
Turbine Wake

Abstract This paper gives an evaluation of most of the commonly used models for predicting wind speed decrease (wake) downstream of a wind turbine. The evaluation is based on six experiments where free-stream and wake wind speed profiles were measured using a ship-mounted sodar at a small offshore wind farm. The experiments were conducted at varying distances between 1.7 and 7.4 rotor diameters downstream of the wind turbine. Evaluation of the models compares the predicted and observed velocity deficits at hub height. A new method of evaluation based on determining the cumulative momentum deficit over the profiles is described. Despite the apparent simplicity of the experiments, the models give a wide range of predictions. Overall, it is not possible to establish any of the models as having individually superior performance with respect to the measurements.

scholarly journals Analysis of rotorcraft wind turbine wake encounters using piloted simulation

2021 ◽  
Author(s):  
Alexander Štrbac ◽  
Tanja Martini ◽  
Daniel H. Greiwe ◽  
Frauke Hoffmann ◽  
Michael Jones
Keyword(s):  
Wind Turbine ◽  
Alternative Energy ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Vortex Wake ◽  
Offshore Wind Farms ◽  
Turbine Wake ◽  
Wind Turbine Wake

AbstractThe use of offshore wind farms in Europe to provide a sustainable alternative energy source is now considered normal. Particularly in the North Sea, a large number of wind farms exist with a significant distance from the coast. This is becoming standard practice as larger areas are required to support operations. Efficient transport and monitoring of these wind farms can only be conducted using helicopters. As wind turbines continue to grow in size, there is a need to continuously update operational requirements for these helicopters, to ensure safe operations. This study assesses German regulations for flight corridors within offshore wind farms. A semi-empirical wind turbine wake model is used to generate velocity data for the research flight simulator AVES. The reference offshore wind turbine NREL 5 MW has been used and scaled to represent wind turbine of different sizes. This paper reports result from a simulation study concerning vortex wake encounter during offshore operations. The results have been obtained through piloted simulation for a transport case through a wind farm. Both subjective and objective measures are used to assess the severity of vortex wake encounters.

scholarly journals Doppler Lidar Investigations of Wind Turbine Near-Wakes and LES Modeling with New Porous Disc Approach

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2101
Author(s):  
Takanori Uchida ◽  
Tadasuke Yoshida ◽  
Masaki Inui ◽  
Yoshihiro Taniyama
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Wind Speeds ◽  
Wind Speed Distribution ◽  
Wake Model ◽  
Turbine Wake ◽  
Swept Area

Many bottom-mounted offshore wind farms are currently planned for the coastal areas of Japan, in which wind speeds of 6.0–10.0 m/s are extremely common. The impact of such wind speeds is very relevant for the realization of bottom-mounted offshore wind farms. In evaluating the feasibility of these wind farms, therefore, strict evaluation at wind speeds of 6.0–10.0 m/s is important. In the present study, the airflow characteristics of 2 MW-class downwind wind turbine wake flows were first investigated using a vertically profiling remote sensing wind measurement device (lidar). The wind turbines used in this study are installed at the point where the sea is just in front of the wind turbines. A ground-based continuous-wave (CW) conically scanning wind lidar system (“ZephIR ZX300”) was used. Focusing on the wind turbine near-wakes, the detailed behaviors were considered. We found that the influence of the wind turbine wake, that is, the wake loss (wind velocity deficit), is extremely large in the wind speed range of 6.0–10.0 m/s, and that the wake loss was almost constant at such wind speeds (6.0–10.0 m/s). It was additionally shown that these results correspond to the distribution of the thrust coefficient of the wind turbine. We proposed a computational fluid dynamics (CFD) porous disk (PD) wake model as an intermediate method between engineering wake models and CFD wake models. Based on the above observations, the wind speed range for reproducing the behavior of the wind turbine wakes with the CFD PD wake model we developed was set to 6.0–10.0 m/s. Targeting the vertical wind speed distribution in the near-wake region acquired in the “ZephIR ZX300”, we tuned the parameters of the CFD PD wake model (CRC = 2.5). We found that in practice, when evaluating the mean wind velocity deficit due to wind turbine wakes, applying the CFD PD wake model in the wind turbine swept area was very effective. That is, the CFD PD wake model can reproduce the mean average wind speed distribution in the wind turbine swept area.

The Effect of Wind and Wave Misalignment on the Response of a Wind Turbine at Bockstigen

2006 ◽  
Author(s):  
Jenny M. V. Trumars ◽  
Johan O. Jonsson ◽  
Lars Bergdahl
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Farm ◽  
Wind Wave ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wave Load ◽  
Design Requirements ◽  
The Waves

The aim of this work is to evaluate data from the offshore wind farm Bockstigen in order to study the effect of directional spreading of waves and wind wave misalignment on the response of the structure. The development of offshore wind energy has led to wind farms at sites with water depths ranging from approximately 6 to 30 m. The change of location from land to sea changes the design requirements of wind energy converters. In addition to wind loads, the wave load on the structure has to be taken into account. Since a wind turbine is highly damped in the inline direction as compared to the crosswise direction, the effect of directional spreading of waves on the response is studied. Depending on the dynamics of the structure the crosswise force could give a larger response than the corresponding inline force. In this study the influence of the directional spreading of the waves on the response is not clear, however the effect of wind and wave misalignment is clear.

scholarly journals Recovery Processes in a Large Offshore Wind Farm

2021 ◽  
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Mesoscale Model ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Recovery Processes ◽  
Mesoscale Processes

Abstract. Wind turbines in a wind farm extract energy from the atmospheric flow and convert it into electricity, resulting in a localized momentum deficit in the wake that reduces energy availability for downwind turbines. Atmospheric momentum convergence from above, below and sides into the wakes replenish the lost momentum, at least partially, so that turbines deep inside a wind farm can continue to function. In this study, we explore recovery processes in a hypothetical offshore wind farm with particular emphasis on comparing the spatial patterns and magnitudes of horizontal and vertical recovery processes and understanding the role of mesoscale processes in momentum recovery in wind farms. For this purpose, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate a hypothetical large offshore wind farm with different wind turbine spacings under realistic initial and boundary conditions. Results show that vertical turbulent transport of momentum from aloft is the main contributor to recovery in wind farms except in cases with strong background winds and high inter-turbine spacing where horizontal advective momentum transport can also contribute equally. Vertical recovery shows a systematic dependence on wind speed and wind farm density that can be quantified using low-order empirical equations. Wind farms significantly alter the mesoscale flow patterns, especially for densely packed wind farms under high wind speed conditions. In these cases, the mesoscale circulations created by the wind farms can transport high momentum air from aloft into the atmospheric boundary layer (ABL) and thus aid in recovery in wind farms. This is a novel study that is one of the first to look at wind farm replenishment processes under realistic meteorological conditions including the role of mesoscale processes. Overall, this study significantly advances our understanding of recovery processes in wind farms and wind farm-ABL interactions.

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