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 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 impact on operational weather radar I/Q data: characterisation and filtering

2017 ◽  
Vol 10 (5) ◽  
pp. 1739-1753 ◽  
Author(s):  
Lars Norin
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Negative Impact ◽  
Weather Radar ◽  
Rapid Expansion ◽  
Weather Radars ◽  
Radar Systems ◽  
Increasing Demand ◽  
Yaw Angle ◽  
The Impact

Abstract. For the past 2 decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in the line of sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value.Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month's worth of recordings of high-resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses, when normalised by amplitude, is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.

scholarly journals Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2351 ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Matteo Becchetti ◽  
Andrea Lombardi ◽  
Ludovico Terzi
Keyword(s):  
Data Analysis ◽  
Wind Turbine ◽  
Error Detection ◽  
Wind Farm ◽  
Assessment Method ◽  
Test Case ◽  
Performance Impact ◽  
Use Of Data ◽  
Yaw Angle ◽  
Multivariate Kernel Regression

The widespread availability of wind turbine operation data has considerably boosted the research and the applications for wind turbine monitoring. It is well established that a systematic misalignment of the wind turbine nacelle with respect to the wind direction has a remarkable impact in terms of down-performance, because the extracted power is in first approximation proportional to the cosine cube of the yaw angle. Nevertheless, due to the fact that in the wind farm practice the wind field facing the rotor is estimated through anemometers placed behind the rotor, it is challenging to robustly detect systematic yaw errors without the use of additional upwind sensory systems. Nevertheless, this objective is valuable because it involves the use of data that are available to wind farm practitioners at zero cost. On these grounds, the present work is a two-steps test case discussion. At first, a new method for systematic yaw error detection through operation data analysis is presented and is applied for individuating a misaligned multi-MW wind turbine. After the yaw error correction on the test case wind turbine, operation data of the whole wind farm are employed for an innovative assessment method of the performance improvement at the target wind turbine. The other wind turbines in the farm are employed as references and their operation data are used as input for a multivariate Kernel regression whose target is the power of the wind turbine of interest. Training the model with pre-correction data and validating on post-correction data, it is estimated that a systematic yaw error of 4 ∘ affects the performance up to the order of the 1.5% of the Annual Energy Production.

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.

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.

About the Extension of Wind Turbine Power Curve in the High Wind Region

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Andrea Lombardi ◽  
Ludovico Terzi
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Test Case ◽  
Power Curve ◽  
High Wind ◽  
High Wind Speed ◽  
Wind Speeds

The financial sustainability and the profitability of wind farms strongly depend on the efficiency of the conversion of wind kinetic energy. This motivates further research about the improvement of wind turbine power curve. If the site is characterized by a considerable occurrence of very high wind speeds, it can become particularly profitable to update the power curve management. This is commonly done by raising the cut-out velocity and the high wind speed cut-in regulating the hysteresis logic. Doing this, on one side, the wind turbine possibly undergoes strong vibration and loads. On the other side, the energy improvement is almost certain and the point is quantifying precisely its magnitude. In this work, the test case of an onshore wind farm in Italy is studied, featuring 17 2.3 MW wind turbines. Through the analysis of supervisory control and data acquisition (SCADA) data, the energy improvement from the extension of the power curve in the high wind speed region is simulated and measured. This could be useful for wind farm owners evaluating the realistic profitability of the installation of the power curve upgrade on their wind turbines. Furthermore, the present work is useful for the analysis of wind turbine behavior under extremely stressing load conditions.

scholarly journals Wind turbine impact on operational weather radar I/Q data: characterisation and filtering

2017 ◽  
Author(s):  
Lars Norin
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Negative Impact ◽  
Weather Radar ◽  
Rapid Expansion ◽  
Weather Radars ◽  
Radar Systems ◽  
Increasing Demand ◽  
Yaw Angle ◽  
The Impact

Abstract. For the past two decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in line-of-sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value. Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month worth of recordings of high resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape, and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.

Incorporating Environmental Impacts into Zero-Point Shifting Diagnosis of Wind Turbines Yaw Angle

Energy ◽  
2021 ◽  
pp. 121762
Author(s):  
Jian Yang ◽  
Li Wang ◽  
Dongran Song ◽  
Chaoneng Huang ◽  
Liansheng Huang ◽  
...  
Keyword(s):  
Environmental Impacts ◽  
Wind Turbines ◽  
Zero Point ◽  
Yaw Angle

Fatigue Life Analysis of Offshore Wind Turbine Support Structures in an Offshore Wind Farm

2018 ◽  
Author(s):  
Bryan Nelson ◽  
Yann Quéméner
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
The Body ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Analysis Tool ◽  
Support Structures ◽  
Offshore Wind Farm ◽  
Actuator Disk

This study evaluated, by time-domain simulations, the fatigue lives of several jacket support structures for 4 MW wind turbines distributed throughout an offshore wind farm off Taiwan’s west coast. An in-house RANS-based wind farm analysis tool, WiFa3D, has been developed to determine the effects of the wind turbine wake behaviour on the flow fields through wind farm clusters. To reduce computational cost, WiFa3D employs actuator disk models to simulate the body forces imposed on the flow field by the target wind turbines, where the actuator disk is defined by the swept region of the rotor in space, and a body force distribution representing the aerodynamic characteristics of the rotor is assigned within this virtual disk. Simulations were performed for a range of environmental conditions, which were then combined with preliminary site survey metocean data to produce a long-term statistical environment. The short-term environmental loads on the wind turbine rotors were calculated by an unsteady blade element momentum (BEM) model of the target 4 MW wind turbines. The fatigue assessment of the jacket support structure was then conducted by applying the Rainflow Counting scheme on the hot spot stresses variations, as read-out from Finite Element results, and by employing appropriate SN curves. The fatigue lives of several wind turbine support structures taken at various locations in the wind farm showed significant variations with the preliminary design condition that assumed a single wind turbine without wake disturbance from other units.

scholarly journals Improving the FLORIS wind plant model for compatibility with gradient-based optimization

2017 ◽  
Vol 41 (5) ◽  
pp. 313-329 ◽  
Author(s):  
Jared J Thomas ◽  
Pieter MO Gebraad ◽  
Andrew Ning
Keyword(s):  
Steady State ◽  
Wind Turbine ◽  
Case Studies ◽  
Wind Farm ◽  
Optimization Problems ◽  
Algorithmic Differentiation ◽  
Function Calls ◽  
Gradient Based ◽  
Wake Model ◽  
Yaw Angle

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients with gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.

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