Analysis of Wind Turbine Wakes Through Time-Resolved and SCADA Data of an Onshore Wind Farm

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Francesco Castellani ◽  
Paolo Sdringola ◽  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Complex Terrain ◽  
Spectral Properties ◽  
Wind Farm ◽  
Point Of View ◽  
Test Case ◽  
Time Resolved ◽  
Onshore Wind ◽  
Yaw Control ◽  
Different Levels

An experimental study is conducted on wind turbine wakes and their effects on wind turbine performances and operation. The test case is a wind farm located on a moderately complex terrain, featuring four turbines with 2 MW of rated power each. Two interturbine distances characterize the layout: 4 and 7.5 rotor diameters. Therefore, it is possible to study different levels of wake recovery. The processed data are twofold: time-resolved series, whose frequency is in the order of the hertz, and supervisory control and data acquisition (SCADA) data with 10 min of sampling time. The wake fluctuations are investigated adopting a “slow” point of view (SCADA), on a catalog of wake events spanned over a long period, and a “fast” point of view of selected time-resolved series of wake events. The power ratios between downstream and upstream wind turbines show that the time-resolved data are characterized by a wider range of fluctuations with respect to the SCADA. Moreover, spectral properties are assessed on the basis of time-resolved data. The combination of meandering wind and yaw control is observed to be associated with different spectral properties depending on the level of wake recovery.

scholarly journals Wind Turbine Yaw Control Optimization and Its Impact on Performance

Machines ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 41 ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Francesco Natili
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Principal Component Regression ◽  
Principal Component ◽  
Energy Conversion Efficiency ◽  
Test Case ◽  
Yaw Control ◽  
Control Optimization ◽  
Technology Improvement

The optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at the level of single wind turbine and of wind farm (for example, through active control of wakes). On these grounds, this work is devoted to the study of the yaw control optimization on a 2 MW wind turbine. The upgrade is estimated by analysing the difference between the measured post-upgrade power and a data driven model of the power according to the pre-upgrade behavior. Particular attention has therefore been devoted to the formulation of a reliable model for the pre-upgrade power of the wind turbine of interest, as a function of the operation variables of all the nearby wind turbines in the wind farm: the high correlation between the possible covariates of the model indicates that Principal Component Regression (PCR) is an adequate choice. Using this method, the obtained result for the selected test case is that the yaw control optimization provides a 1% of annual energy production improvement. This result indicates that wind turbine control optimization can non-negligibly improve the efficiency of wind turbine technology.

Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations

2019 ◽  
Vol 135 ◽  
pp. 674-686 ◽  
Author(s):  
Miguel A. Prósper ◽  
Carlos Otero-Casal ◽  
Felipe Canoura Fernández ◽  
Gonzalo Miguez-Macho
Keyword(s):  
High Resolution ◽  
Wind Power ◽  
Complex Terrain ◽  
Wind Farm ◽  
Onshore Wind ◽  
Wind Power Forecasting ◽  
Power Forecasting

scholarly journals ESTUDO DA PRODUÇÃO DE ENERGIA EÓLICA A PARTIR DE MEDIÇÕES ANEMOMÉTRICAS DA ESTAÇÃO DE CRAÍBAS/AL E SIMULAÇÕES COM O MODELO WASP

2016 ◽  
Vol 38 ◽  
pp. 477
Author(s):  
Thays Paes de Oliveira ◽  
Rosiberto Salustiano da Silva Junior ◽  
Roberto Fernando Fonseca Lyra ◽  
Sandro Correia Holanda
Keyword(s):  
Power Generation ◽  
Probability Distribution ◽  
Wind Turbine ◽  
Wind Direction ◽  
Wind Farm ◽  
Scale Parameters ◽  
Wind Potential ◽  
Generation Capacity ◽  
Intensity Density ◽  
Different Levels

Wind energy is seen as one of the promising generation of electricity, as a source of cheap and renewable, is benefit to reduce the environmental impacts of the dam. Along with the hydroelectric networks, the energy produced by the wind will help to increase power generation capacity in the country. That from speed data and direction municipality Wind Craíbas in the corresponding period 2014 - 2015, estimated the wind potential of the region. The tool used in the treatment of the collected data was the Wasp, making simulations of three different levels of measurement, producing a fictitious wind farm with powerful wind turbine. With the model, WASP helps estimate the probability distribution of Weibull and scale parameters A and K. he predominant wind direction is southeast and the best wind power and intensity density levels took place in 70m and 100m high , with about 201 W / m² and 243 W / m² respectively. But when evalua ted the inclusion of fictitious wind farm, the best use happened at 100m tall with production around 73.039 GWh , which can be attributed this improvement to increased efficiency of the wind turbine used in the simulation.

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.

Precision Computation of Wind Turbine Power Upgrades: An Aerodynamic and Control Optimization Test Case

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Mario Luca Fravolini ◽  
Silvia Cascianelli ◽  
Ludovico Terzi
Keyword(s):  
Wind Turbine ◽  
Power Output ◽  
Wind Farm ◽  
Residual Life ◽  
Test Case ◽  
Labor Costs ◽  
Passive Flow Control ◽  
Production Improvement ◽  
Input Variables ◽  
And Control

Wind turbine upgrades have recently been spreading in the wind energy industry for optimizing the efficiency of the wind kinetic energy conversion. These interventions have material and labor costs; therefore, it is fundamental to estimate the production improvement realistically. Furthermore, the retrofitting of the wind turbines sited in complex environments might exacerbate the stress conditions to which those are subjected and consequently might affect the residual life. In this work, a two-step upgrade on a multimegawatt wind turbine is considered from a wind farm sited in complex terrain. First, vortex generators and passive flow control devices have been installed. Second, the management of the revolutions per minute has been optimized. In this work, a general method is formulated for assessing the wind turbine power upgrades using operational data. The method is based on the study of the residuals between the measured power output and a judicious model of the power output itself, before and after the upgrade. Therefore, properly selecting the model is fundamental. For this reason, an automatic feature selection algorithm is adopted, based on the stepwise multivariate regression. This allows identifying the most meaningful input variables for a multivariate linear model whose target is the power of the upgraded wind turbine. For the test case of interest, the adopted upgrade is estimated to increase the annual energy production to 2.6 ± 0.1%. The aerodynamic and control upgrades are estimated to be 1.8% and 0.8%, respectively, of the production improvement.

scholarly journals Wind Turbine Wake Modeling in Accelerating Wind Field: A Preliminary Study on a Two-Dimensional Hill

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 153 ◽  
Author(s):  
Omar M. A. M. Ibrahim ◽  
Shigeo Yoshida ◽  
Masahiro Hamasaki ◽  
Ao Takada
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Field ◽  
Complex Terrain ◽  
Wind Farm ◽  
Wind Tunnel Test ◽  
Two Dimensional ◽  
Preliminary Study ◽  
Wake Model

Complex terrain can influence wind turbine wakes and wind speed profiles in a wind farm. Consequently, predicting the performance of wind turbines and energy production over complex terrain is more difficult than it is over flat terrain. In this preliminary study, an engineering wake model, that considers acceleration on a two-dimensional hill, was developed based on the momentum theory. The model consists of the wake width and wake wind speed. The equation to calculate the rotor thrust, which is calculated by the wake wind speed profiles, was also formulated. Then, a wind-tunnel test was performed in simple flow conditions in order to investigate wake development over a two-dimensional hill. After this the wake model was compared with the wind-tunnel test, and the results obtained by using the new wake model were close to the wind-tunnel test results. Using the new wake model, it was possible to estimate the wake shrinkage in an accelerating two-dimensional wind field.

Wind Flow Over a Complex Terrain in Nygårdsfjell, Norway

2015 ◽  
Author(s):  
Muhammad Bilal ◽  
Narendran Sridhar ◽  
Guillermo Araya ◽  
Sivapathas Parameswaran ◽  
Yngve Birkelund
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Complex Terrain ◽  
Wind Farm ◽  
Turbulence Models ◽  
Future Research ◽  
Wind Flow ◽  
Governing Equations ◽  
The North ◽  
Numerical Predictions

The understanding of atmospheric flows is crucial in the analysis of dispersion of a contaminant or pollutant, wind energy and air-quality assessment to name a few. Additionally, the effects of complex terrain and associated orographic forcing are crucial in wind energy production. Furthermore, the use of the Reynolds-averaged Navier-Stokes (RANS) equations in the analysis of complex terrain is still considered the “workhorse” since millions of mesh points are required to accurately capture the details of the surface. On the other hand, solving the same problem by means of the instantaneous governing equations of the flow (i.e., in a suite of DNS or LES) would imply almost prohibitive computational resources. In this study, numerical predictions of atmospheric boundary layers are performed over a complex topography located in Nygårdsfjell, Norway. The Nygårdsfjell wind farm is located in a valley at approximately 420 meters above sea level surrounded by mountains in the north and south near the Swedish border. Majority of the winds are believed to be originated from Torneträsk lake in the east which is covered with ice during the winter time. The air closest to the surface on surrounding mountains gets colder and denser. The air then slides down the hill and accumulates over the lake. Later, the air spills out westward towards Ofotfjord through the broader channel that directs and transforms it into highly accelerated winds. Consequently, one of the objectives of the present article is to study the influence of local terrain on shaping these winds over the wind farm. It is worth mentioning that we are not considering any wind turbine model in the present investigation, being the main purpose to understand the influence of the local surface topography and roughness on the wind flow. Nevertheless, future research will include modeling the presence of a wind turbine and will be published elsewhere. The governing equations of the flow are solved by using a RANS approach and by considering three different two-equation turbulence models: k-omega (k–ω), k-epsilon (k–ε) and shear stress transport (SST). Furthermore, the real topographical characteristics of the terrain have been modeled by extracting the required area from the larger digital elevation model (DEM) spanning over 100 km square. The geometry is then extruded using Rhino and meshed in ANSYS Fluent. The terrain dimensions are approximately 2000×1000 meter square.

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.

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