Data-Driven Methods for the Analysis of Wind Turbine Yaw Control Optimization

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Francesco Natili
Keyword(s):  
Wind Turbine ◽  
Performance Improvement ◽  
Wind Turbines ◽  
General Procedure ◽  
Test Case ◽  
Yaw Control ◽  
Control Optimization ◽  
Operational Variables ◽  
Before And After ◽  
Input Variables

Abstract Multi-megawatt wind turbines are nowadays a mature technology, and therefore, there is considerable scientific and industrial attention to the opportunity of further improving the efficiency of wind kinetic energy conversion into electricity. One of the major developments in this field of research regards the optimization of wind turbine control. This work deals with a test case of yaw control optimization on a 2-MW wind turbine sited in Italy. The objective of the work is to compute the performance improvement provided by the upgrade after some months of operation. This has been accomplished through the formulation of an appropriate model for the power of the wind turbine of interest and the analysis of the residuals between model estimates and measurements before and after the upgrade. In this work, a general procedure for selecting a robust multivariate linear model is adopted, and the resulting model, employing as input variables several operational variables from the nearby wind turbines in the farm, is used for quantifying the performance improvement. The estimate is that this upgrade provides a 0.8% improvement of the annual energy production.

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.

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.

scholarly journals SCADA Data Analysis Methods for Diagnosis of Electrical Faults to Wind Turbine Generators

2021 ◽  
Vol 11 (8) ◽  
pp. 3307
Author(s):  
Francesco Castellani ◽  
Davide Astolfi ◽  
Francesco Natili
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Principal Component ◽  
Support Vector ◽  
General Context ◽  
Test Case ◽  
Electric Generator ◽  
Before And After ◽  
Electrical Faults

The electric generator is estimated to be among the top three contributors to the failure rates and downtime of wind turbines. For this reason, in the general context of increasing interest towards effective wind turbine condition monitoring techniques, fault diagnosis of electric generators is particularly important. The objective of this study is contributing to the techniques for wind turbine generator fault diagnosis through a supervisory control and data acquisition (SCADA) analysis method. The work is organized as a real-world test-case discussion, involving electric damage to the generator of a Vestas V52 wind turbine sited in southern Italy. SCADA data before and after the generator damage have been analyzed for the target wind turbine and for reference healthy wind turbines from the same site. By doing this, it has been possible to formulate a normal behavior model, based on principal component analysis and support vector regression, for the power and for the voltages and currents of the wind turbine. It is shown that the incipience of the fault can be individuated as a change in the behavior of the residuals between model estimates and measurements. This phenomenon was clearly visible approximately two weeks before the fault. Considering the fast evolution of electrical damage, this result is promising as regards the perspectives of exploiting SCADA data for individuating electric damage with an advance that can be useful for applications in wind energy practice.

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.

Effects of Rotor-Blade Deformation onto Performance of Domestic Wind Turbines

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Carlos Armenta-Deu
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Deformation Process ◽  
Angular Speed ◽  
Gravitational Effects ◽  
Mechanical Deformations ◽  
Centrifugal Stiffening ◽  
Small Wind Turbines ◽  
Before And After ◽  
Blade Model

Paper is focused on the influence that blade deformations by torsion and bending due to drag, lift, and gravitational effects has on the performance of small wind turbines. A blade model of stiff finite elements connected by rotating junctions is used. Mechanical deformations are simulated by controlled gravity and torsional forces, and their effects are measured through the response of the wind turbine. Tests have been run before and after the deformation process under different wind conditions in a wind tunnel. No centrifugal stiffening and gyroscopic moments are considered due to the low angular speed. Wind speed was controlled to determine the effect of the deformation on the performance of the wind turbine as a function of the wind power. The results have shown that in all cases, the effects of the deformation are negative, and the decrease in power has been calculated depending on wind conditions.

Yaw Control of Small Wind Turbines With a New Passive Tail Device: Part 1 — Steady-State Case

Solar Energy ◽  
2003 ◽  
Author(s):  
Eduardo Rinco´n Meji´a ◽  
Jesu´s Tovar Salazar ◽  
Jo´zef Wo´jcik Filipek
Keyword(s):  
Steady State ◽  
Wind Turbine ◽  
Field Test ◽  
Wind Turbines ◽  
Strong Wind ◽  
Test Results ◽  
Yaw Control ◽  
Small Wind Turbines ◽  
Horizontal Axis Wind Turbines ◽  
State Case

This paper describes the behavior of a new tail device to yaw smoothly small wind turbine rotors out of the wind during strong wind or gusts. The passive tail device consists of a rigid short tail, an aerodynamic rotating vane, a tail bumper, and a spring. This passive tail device reduces gyroscopic loads, is easy to adjust, can be manufactured in smaller sizes, and is much stronger than conventional vanes used in small wind machines. Besides, the energy collected with it is greater. Field test results indicate that its behavior agrees very well with simulations, and that the regulator can be advantageously utilized, as compared with conventional vanes and other mechanical or electromechanical means, in horizontal-axis wind turbines with diameters of 12 m or smaller. Here the steady-state case (quasi-steady wind velocity is assumed) is analyzed, showing the technical viability of the regulator proposed.

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 Computing the Real Impact of Wind Turbine Power Curve Upgrades: A SCADA-Based Multivariate Linear Method and a Vortex Generator Test Case

2018 ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Mario Luca Fravolini ◽  
Silvia Cascianelli ◽  
Ludovico Terzi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Linear Method ◽  
Vortex Generator ◽  
Test Case ◽  
Labor Costs ◽  
Linear Modeling ◽  
Data Set ◽  
The Real

Wind turbine upgrades have been spreading in the recent years in the wind energy industry, with the aim of optimizing the efficiency of wind kinetic energy conversion. This kind of interventions has material and labor costs and it is therefore fundamental to estimate realistically the production improvement. Further, the retrofitting of wind turbines sited in harsh environments might exacerbate the stressing conditions to which wind turbines are subjected and consequently might affect the residue lifetime. This work deals with a case of retrofitting: the testing ground is a multi-megawatt wind turbine from a wind farm sited in a very complex terrain. The blades have been optimized by installing vortex generators and passive flow control devices. The complexity of this test case, dictated by the environment and by the features of the data set at disposal, inspires the formulation of a general method for estimating production upgrades, based on multivariate linear modeling of the power output of the upgraded wind turbine. The method is a distinctive part of the outcome of this work because it is generalizable to the study of whatever wind turbine upgrade and it is adaptable to the features of the data sets at disposal. In particular, applying this model to the test case of interest, it arises that the upgrade increases the annual energy production of the wind turbine of an amount of the order of the 2%. This quantity is of the same order of magnitude, albeit non-negligibly lower, than the estimate based on the assumption of ideal wind conditions. Therefore, it arises that complex wind conditions might affect the efficiency of wind turbine upgrades and it is therefore important to estimate their impact using data from wind turbines operating in the real environment of interest.

An Operation Data-Based Method for the Diagnosis of Zero-Point Shift of Wind Turbines Yaw Angle

2019 ◽  
Vol 142 (2) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Ludovico Terzi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Negative Impact ◽  
Zero Point ◽  
Test Case ◽  
Case Discussion ◽  
Angle Shift ◽  
Points Of View ◽  
Yaw Angle

Abstract The alignment of the wind turbine yaw to the wind direction is an important topic for wind turbine technology by several points of view. For example, the negative impact on power production of an undesired non-optimal yaw alignment can be impressive. The diagnosis of zero-point shifting of the yaw angle is commonly performed by adopting supplementary measurement sources, as for example, light detection and ranging (LIDAR) anemometers. The drawback is that these measurement campaigns have a certain cost against an uncertain diagnosis outcome. There is therefore an increasing interest from wind turbine practitioners in the formulation of zero-point yaw angle shift diagnosis techniques through the use of nacelle anemometer data. This work is devoted to this task and is organized as a test case discussion: a wind farm featuring six multi-megawatt wind turbines is considered. The study of the power factor Cp as function of the yaw error (estimated through nacelle anemometer data) is addressed. The proposed method has been validated through the detection of a 8 deg zero-point shift of the yaw angle of one wind turbine in the test case wind farm. After the correction of this offset, the performance of the wind turbine of interest is shown to be comparable with the nominal. The results of this work therefore support that an appropriate analysis of nacelle anemometer and operation data can be effective for the diagnosis of zero-point shift of the yaw angle of wind turbines.

scholarly journals Uncertainty Quantification of the Effects of Blade Damage on the Actual Energy Production of Modern Wind Turbines

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3785 ◽  
Author(s):  
Francesco Papi ◽  
Lorenzo Cappugi ◽  
Simone Salvadori ◽  
Mauro Carnevale ◽  
Alessandro Bianchini
Keyword(s):  
Wind Turbine ◽  
Uncertainty Quantification ◽  
Wind Turbines ◽  
Energy Production ◽  
Prolonged Exposure ◽  
Turbine Blades ◽  
Test Case ◽  
Elastic Model ◽  
Drag Coefficients ◽  
Lift And Drag

Wind turbine blade deterioration issues have come to the attention of researchers and manufacturers due to the relevant impact they can have on the actual annual energy production (AEP). Research has shown how after prolonged exposure to hail, rain, insects or other abrasive particles, the outer surface of wind turbine blades deteriorates. This leads to increased surface roughness and material loss. The trailing edge (TE) of the blade is also often damaged during assembly and transportation according to industry veterans. This study aims at investigating the loss of AEP and efficiency of modern multi-MW wind turbines due to such issues using uncertainty quantification. Such an approach is justified by the stochastic and widely different environmental conditions in which wind turbines are installed. These cause uncertainties regarding the blade’s conditions. To this end, the test case selected for the study is the DTU 10 MW reference wind turbine (RWT), a modern reference turbine with a rated power of 10 MW. Blade damage is modelled through shape modification of the turbine’s airfoils. This is done with a purposely developed numerical tool. Lift and drag coefficients for the damaged airfoils are calculated using computational fluid dynamics. The resulting lift and drag coefficients are used in an aero-servo-elastic model of the wind turbine using NREL’s code OpenFAST. An arbitrary polynomial chaos expansion method is used to estimate the probability distributions of AEP and power output of the model when blade damage is present. Average AEP losses of around 1% are predicted mainly due to leading-edge blade damage. Results show that the proposed method is able to account for the uncertainties and to give more meaningful information with respect to the simulation of a single test case.

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