scholarly journals Numerical and Experimental Methods for the Assessment of Wind Turbine Control Upgrades

2018 ◽  
Vol 8 (12) ◽  
pp. 2639 ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Francesco Berno ◽  
Ludovico Terzi
Keyword(s):  
Control System ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Power Curve ◽  
Data Set ◽  
Wind Turbine Control ◽  
The Impact ◽  
Operational Data

Megawatt-scale wind turbine technology is nowadays mature and, therefore, several technical improvements in order to optimize the efficiency of wind power conversion have been recently spreading in the industry. Due to the nonstationary conditions to which wind turbines are subjected because of the stochastic nature of the source, the quantification of the impact of wind turbine power curve upgrades is a complex task and in general, it has been observed that the efficiency of the upgrades can vary considerably depending on the wind flow conditions at the microscale level. In this work, a test case of wind turbine control system improvement was studied numerically and through operational data. The wind turbine is multi-megawatt; it is part of a wind farm sited in a complex terrain in Italy, featuring 17 wind turbines. The analyzed control upgrade is an optimization of the revolutions per minute (rpm) management. The impact of this upgrade was quantified through a method based on operational data: It consists of the study, before and after the upgrade, of the residuals between the measured power output of the wind turbine of interest and an appropriate model of the power output itself. The input variables for the model were selected to be some operational parameters of the nearby wind turbines: They were selected from the data set at disposal with a stepwise regression algorithm. This work also includes a numerical characterization of the problem, by means of aeroelastic simulations performed with the FAST software: By mimicking the pre- and post-upgrade generator rpm–generator torque curve, it is subsequently possible to estimate how the wind turbine power curve changes. The main result of this work is that the two estimates of production improvement have the same order of magnitude (1.0% of the production below rated power). In general, this study sheds light on the perspective of employing not only operational data, but also a sort of digital replica of the wind turbine of interest, in order to reliably quantify the impact of control system upgrades.

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 Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

2021 ◽  
Vol 6 (4) ◽  
pp. 997-1014
Author(s):  
Janna Kristina Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Flow Conditions ◽  
Output Fluctuations ◽  
Power Difference ◽  
Time Correlations

Abstract. Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

Dynamic Simulation of a Wind Farm With Variable Speed Wind Turbines

2003 ◽  
Author(s):  
E. Muljadi ◽  
C. P. Butterfield
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Network ◽  
Variable Speed ◽  
Power Capacity ◽  
Advantages And Disadvantages ◽  
The Impact

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2001 was 4,260 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. A typical wind farm with variable speed wind turbines connected to an existing power grid is investigated. Different control strategies for feeding wind energy into the power network are investigated, and the advantages and disadvantages are presented.

Flow Simulation Around a Rim-Driven Wind Turbine and in Its Wake

2013 ◽  
Author(s):  
Bryan E. Kaiser ◽  
Svetlana V. Poroseva ◽  
Michael A. Snider ◽  
Rob O. Hovsapian ◽  
Erick Johnson
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Flow Simulation ◽  
Wind Farms ◽  
Sensitivity Study ◽  
Onshore Wind ◽  
Flow Simulations ◽  
Turbine Design ◽  
The Impact

A relatively high free stream wind velocity is required for conventional horizontal axis wind turbines (HAWTs) to generate power. This requirement significantly limits the area of land for viable onshore wind farm locations. To expand a potential for wind power generation and an area suitable for onshore wind farms, new wind turbine designs capable of wind energy harvesting at low wind speeds are currently in development. The aerodynamic characteristics of such wind turbines are notably different from industrial standards. The optimal wind farm layout for such turbines is also unknown. Accurate and reliable simulations of a flow around and behind a new wind turbine design should be conducted prior constructing a wind farm to determine optimal spacing of turbines on the farm. However, computations are expensive even for a flow around a single turbine. The goal of the current study is to determine a set of simulation parameters that allows one to conduct accurate and reliable simulations at a reasonable cost of computations. For this purpose, a sensitivity study on how the parameters variation influences the results of simulations is conducted. Specifically, the impact of a grid refinement, grid stretching, grid cell shape, and a choice of a turbulent model on the results of simulation of a flow around a mid-sized Rim Driven Wind Turbine (U.S. Patent 7399162) and in its near wake is analyzed. This wind turbine design was developed by Keuka Energy LLC. Since industry relies on commercial software for conducting flow simulations, STAR-CCM+ software [1] was used in our study. A choice of a turbulence model was made based on the results from our previous sensitivity study of flow simulations over a rotating disk [2].

scholarly journals Optimal Irregular Wind Farm Design for Continuous Placement of Wind Turbines with a Two-Dimensional Jensen-Gaussian Wake Model

2018 ◽  
Vol 8 (12) ◽  
pp. 2660 ◽  
Author(s):  
Longyan Wang ◽  
Yunkai Zhou ◽  
Jian Xu
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Power Losses ◽  
Wake Effect ◽  
Coordinate Method ◽  
Wind Farm Design ◽  
Wake Model ◽  
Farm Design

Optimal design of wind turbine placement in a wind farm is one of the most effective tools to reduce wake power losses by alleviating the wake effect in the wind farm. In comparison to the discrete grid-based wind farm design method, the continuous coordinate method has the property of continuously varying the placement of wind turbines, and hence, is far more capable of obtaining the global optimum solutions. In this paper, the coordinate method was applied to optimize the layout of a real offshore wind farm for both simplified and realistic wind conditions. A new analytical wake model (Jensen-Gaussian model) taking into account the wake velocity variation in the radial direction was employed for the optimization study. The means of handling the irregular real wind farm boundary were proposed to guarantee that the optimized wind turbine positions are feasible within the wind farm boundary, and the discretization method was applied for the evaluation of wind farm power output under Weibull distribution. By investigating the wind farm layout optimization under different wind conditions, it showed that the total wind farm power output increased linearly with an increasing number of wind turbines. Under some particular wind conditions (e.g., constant wind speed and wind direction, and Weibull distribution), almost the same power losses were obtained under the wake effect of some adjacent wind turbine numbers. A common feature of the wind turbine placements regardless of the wind conditions was that they were distributed along the wind farm boundary as much as possible in order to alleviate the wake effect.

Dynamic Simulation of a Wind Farm With Variable-Speed Wind Turbines

2003 ◽  
Vol 125 (4) ◽  
pp. 410-417
Author(s):  
E. Muljadi ◽  
C. P. Butterfield
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Network ◽  
Variable Speed ◽  
Power Capacity ◽  
Advantages And Disadvantages ◽  
The Impact

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2002 was 4,685 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. We investigate a typical wind farm with variable-speed wind turbines connected to an existing power grid. We also examine different control strategies for feeding wind energy into the power network and present the advantages and disadvantages.

Assessment of a Modified Blade Element Momentum Methodology for Diffuser Augmented Wind Turbines

2017 ◽  
Author(s):  
Stavros N. Leloudas ◽  
Georgios N. Lygidakis ◽  
Ioannis K. Nikolos
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Horizontal Axis Wind Turbine ◽  
Correction Model ◽  
Short Period ◽  
Turbine Design ◽  
The Impact ◽  
Bem Theory ◽  
Blade Element

The Blade Element Momentum (BEM) theory is nowadays the cornerstone of the horizontal axis wind turbine design, as its application allows for the accurate aerodynamic simulation and power output prediction of wind turbine rotors in a remarkably short period of time. Therefore, efforts have been made for the extension of the classic BEM theory to the performance analysis of Diffuser Augmented Wind Turbines (DAWTs) as well. In this study, the development and assessment of such an in-house BEM code are presented. The proposed computational model is based on the modification of the momentum part of the classical BEM theory; thus, it is capable to account for the diffuser’s effect on the calculation of the axial and tangential induction factors, through the utilization of the velocity speed-up distribution over the rotor plane of the unloaded diffuser. Furthermore, a detailed Glauert’s correction model, which employs Buhl’s modification, specially tailored for the DAWT case is included, to deal with the high values of the axial induction factor. The accuracy of the model is assessed against numerical and experimental results available in the literature, while the impact of the Prandtl’s tip loss correction model on the rotor’s predicted power output is also examined.

Effect of Wind Turbine Noise on Workers' Sleep Disorder: A Case Study of Manjil Wind Farm in Northern Iran

2015 ◽  
Vol 14 (02) ◽  
pp. 1550020 ◽  
Author(s):  
Milad Abbasi ◽  
Mohammad Reza Monnazzam ◽  
SayedAbbolfazl Zakerian ◽  
Arsalan Yousefzadeh
Keyword(s):  
Wind Turbine ◽  
Sleep Disorder ◽  
Wind Turbines ◽  
Daytime Sleepiness ◽  
Wind Farm ◽  
Wind Farms ◽  
Sound Level ◽  
Wind Turbine Noise ◽  
The Impact

Noise from wind turbines is one of the most important factors affecting the health, welfare, and human sleep. This research was carried out to study the effect of wind turbine noise on workers' sleep disorder. For this, Manjil Wind Farm, because of the greater number of staff and turbines than other wind farms in Iran, was chosen as case study. A total number of 53 participants took part in this survey. They were classified into three groups of mechanics, security, and official. In this study, daytime sleepiness data of workers were gathered using Epworth Sleepiness Scales (ESS) was used to determine the level of daytime sleepiness among the workers. The 8-h equivalent sound level (LAeq,8h) was measured to determine the individuals' exposure at each occupational group. Finally, the effect of sound, age, and workers' experience on individuals' sleep disorder was analyzed through multiple regression analysis in the R software. The results showed that there was a positive and significant relationship between age, workers' experience, equivalent sound level, and the level of sleep disorder. When age is constant, sleep disorder will increase by 26% as per each 1 dB increase in equivalent sound level. In situations where equivalent sound level is constant, an increase of 17% in sleep disorder is occurred as per each year of work experience. Because of the difference in sound exposure in different occupational groups. The effect of noise in repairing group was about 6.5 times of official group and also 3.4 times of the security group. Sleep disorder effect caused by wind turbine noise in the security group is almost two times more than the official group. Unlike most studies on wind turbine noise that address the sleep disorder among inhabitants nearby wind farms, this study, for the first time in the world, examines the impact of wind turbine noise on sleep disorder of workers who are more closer to wind turbines and exposed to higher levels of noise. So despite all the good benefits of wind turbines, it can be stated that this technology has health risks for all those exposed to its sound. However, further research is needed to confirm the results of this study.

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 Quantifying the Impact of Wind Turbine Wakes on Power Output at Offshore Wind Farms

2010 ◽  
Vol 27 (8) ◽  
pp. 1302-1317 ◽  
Author(s):  
R. J. Barthelmie ◽  
S. C. Pryor ◽  
S. T. Frandsen ◽  
K. S. Hansen ◽  
J. G. Schepers ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Power Output ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Power Losses ◽  
Offshore Wind Farms ◽  
The Impact ◽  
Mean Square Errors ◽  
Large Wind

Abstract There is an urgent need to develop and optimize tools for designing large wind farm arrays for deployment offshore. This research is focused on improving the understanding of, and modeling of, wind turbine wakes in order to make more accurate power output predictions for large offshore wind farms. Detailed data ensembles of power losses due to wakes at the large wind farms at Nysted and Horns Rev are presented and analyzed. Differences in turbine spacing (10.5 versus 7 rotor diameters) are not differentiable in wake-related power losses from the two wind farms. This is partly due to the high variability in the data despite careful data screening. A number of ensemble averages are simulated with a range of wind farm and computational fluid dynamics models and compared to observed wake losses. All models were able to capture wake width to some degree, and some models also captured the decrease of power output moving through the wind farm. Root-mean-square errors indicate a generally better model performance for higher wind speeds (10 rather than 6 m s−1) and for direct down the row flow than for oblique angles. Despite this progress, wake modeling of large wind farms is still subject to an unacceptably high degree of uncertainty.

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