Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantification of power losses due to wind turbine wake interactions through SCADA,meteorological and wind LiDAR data

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met‐tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut‐in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability‐driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60‐80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.     

A pragmatic approach to wind farm simulations using the dynamic wake meandering model

This paper presents a computationally efficient method for using the dynamic wake meandering model to conduct simulations of wind farm power production. The method is based on creating a database, which contains the time and rotor‐averaged wake effect at any point downstream of a wake‐emitting turbine operating in arbitrary ambient conditions and at an arbitrary degree of wake influence. This database is later used as a look‐up table at runtime to estimate the operating conditions at all turbines in the wind farm, thus eliminating the need to run the dynamic wake meandering model at runtime. By using the proposed method, the time required to conduct wind farm simulations is reduced by three orders of magnitude compared with running the standalone dynamic wake meandering model at runtime. As a result, the wind farm production dynamics for a farm of 100 turbines at 10,000 different sets of ambient conditions run on a normal laptop in 1 h. The method is validated against full scale measurements from the Smøla and OWEZ wind farms, and fair agreement is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

An experimental investigation on the effect of individual turbine control on wind farm dynamics

Individual wind turbines in a wind farm typically operate to maximize their performance with no consideration of the impact of wake effects on downstream turbines. There is potential to increase power and reduce structural loads within a wind farm by properly coordinating the turbines. To effectively design and analyze coordinated wind turbine controllers requires control‐oriented turbine wake models of sufficient accuracy. This paper focuses on constructing such a model from experiments. The experiments were conducted to better understand the wake interaction and impact on voltage production in a three‐turbine array. The upstream turbine operating condition was modulated in time, and the dynamic impact on the downstream turbine was recorded through the voltage output time signal. The flow dynamics observed in the experiments were used to improve a static wake model often used in the literature for wind farm control. These experiments were performed in the atmospheric boundary layer wind tunnel at the Saint Anthony Falls Laboratory at the University of Minnesota using particle image velocimetry for flow field analysis and turbine voltage modulation to capture the physical evolution in addition to the dynamics of turbine wake interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

多工况下漂浮式风力机张力腿平台时域响应及系泊强度分析

为研究漂浮式风力机张力腿平台在风、浪、海流载荷联合作用下的时域响应及系泊受力特征,建立漂浮式风力机及张力腿平台模型,采用有限元方法,对比分析无风、额定、最大及极限工况下张力腿平台运动响应及系泊受力。4种工况作用下,极限停机工况时漂浮式平台运动响应最大,最大作业工况其次,额定作业工况再次,无风作业工况最小;但在最大工况时系泊作用力最大。结果表明:运动响应主要集中在纵荡,垂荡和纵摇方向;作业工况越恶劣,漂浮式平台运动响应越大;系泊张力在最大作业工况时最大,但小于系泊断裂极限。     

A passively self-adjusting floating wind farm layout to increase the annual energy production

Wake losses inside a wind farm occur due to the aerodynamic interactions when a downwind turbine is in the wake of upwind turbines. The ability of floating offshore wind turbines (FOWTs) to relocate their positions in the horizontal plane introduces an opportunity to decrease the wake losses in a floating wind farm (FWF). Our goal is to use this ability to passively move the downwind FOWT out of the wake of upwind ones. Since the mooring system (MS) attached to a FOWT is responsible for its station keeping, the horizontal motions of the FOWT depend on the MS design. Hence, if we can design the MS to passively move the FOWT out of the wake, we can increase the FWF annual energy production (AEP). In this paper, we investigate if we can benefit from relocating FOWTs in a FWF and increase its AEP. In addition, we present a novel approach that considers the ability of a FOWT to relocate its position as a new degree of freedom (DoF) in the FWF layout design. This means we will have a self-adjusting wind farm layout where the FOWTs passively re-arrange themselves depending on the wind direction and the wind speed. Consequently, we will have a slightly different wind farm layout for every wind direction and every wind speed. To achieve this layout, we include the MS design as part of the FWF's layout design. In a self-adjusting FWF layout, each FOWT is attached to a customized MS design allowing it to relocate its position in the best way possible according to the wind direction, to increase the overall AEP of the wind farm. The results of one case study show that the novel approach can increase the FWF's AEP by 1.6% when compared with a current state of the art optimized floating wind farm layout. Finally, we implemented our method as an open-source python tool to be used and enhanced further within the wind energy community.     

One‐way mesoscale‐microscale coupling for simulating a wind farm in North Texas: Assessment against SCADA and LiDAR data

One‐way nested mesoscale to microscale simulations of an onshore wind farm have been performed nesting the Weather Research and Forecasting (WRF) model and our in‐house high‐resolution large‐eddy simulation code (UTD‐WF). Each simulation contains five nested WRF domains, with the largest domain spanning the north Texas Panhandle region with a 4 km resolution, while the highest resolution (50 m) nest simulates microscale wind fluctuations and turbine wakes within a single wind farm. The finest WRF domain in turn drives the UTD‐WF LES higher‐resolution domain for a subset of six turbines at a resolution of ～5 m. The wind speed, direction, and boundary layer profiles from WRF are compared against measurements obtained with a met‐tower and a scanning Doppler wind LiDAR located within the wind farm. Additionally, power production obtained from WRF and UTD‐WF are assessed against supervisory control and data acquisition (SCADA) system data. Numerical results agree well with the experimental measurements of the wind speed, direction, and power production of the turbines. UTD‐WF high‐resolution domain improves significantly the agreement of the turbulence intensity at the turbines location compared with that of WRF. Velocity spectra have been computed to assess how the nesting allows resolving a wide range of scales at a reasonable computational cost. A domain sensitivity analysis has been performed. Velocity spectra indicate that placing the inlet too close to the first row of turbines results in an unrealistic peak of energy at the rotational frequency of the turbines. Spectra of the power production of a single turbine and of the cumulative power of the array have been compared with analytical models.     

Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms

Turbulence characteristics of the wind farm inflow have a significant impact on the energy production and the lifetime of a wind farm. The common approach is to use the meteorological mast measurements to estimate the turbulence intensity (TI) but they are not always available and the turbulence varies over the extent of the wind farm. This paper describes a method to estimate the TI at individual turbine locations by using the rotor effective wind speed calculated via high frequency turbine data.The method is applied to Lillgrund and Horns Rev-I offshore wind farms and the results are compared with TI derived from the meteorological mast, nacelle mounted anemometer on the turbines and estimation based on the standard deviation of power. The results show that the proposed TI estimation method is in the best agreement with the meteorological mast. Therefore, the rotor effective wind speed is shown to be applicable for the TI assessment in real-time wind farm calculations under different operational conditions. Furthermore, the TI in the wake is seen to follow the same trend with the estimated wake deficit which enables to quantify the turbulence in terms of the wake loss locally inside the wind farm.     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

Potential of power gain with improved yaw alignment

One of the primary criteria for extracting energy from the wind using horizontal axis upwind wind turbines is the ability to align the rotor axis with the dominating wind direction. The conventional way of estimating the direction of the incoming flow is by using transducers placed atop the nacelle and downwind of the rotor. Recent studies have suggested methods based on advanced upwind measurement technologies for estimating the inflow direction and improving the yaw alignment. In this study, the potential of increased power output with improved yaw alignment is investigated by assessing the performance of a current measurement and yaw control system. The performance is assessed by analyzing data containing upwind wind speed and direction measurements from a met mast, and yaw angle and power production measurements from an operating offshore wind turbine. The results of the analysis indicate that the turbine is operating with a wind speed‐dependent yaw error distribution. The theoretical annual energy production loss due to the yaw error distribution of the existing system is estimated to approximately 0.2%. Copyright © 2014 John Wiley & Sons, Ltd.     

Design and model confirmation of the intermediate scale VolturnUS floating wind turbine subjected to its extreme design conditions offshore Maine

Floating offshore wind turbines are gaining considerable interest in the renewable energy sector. Design standards for floating offshore wind turbines such as the American Bureau of Shipping (ABS) Guide for Building and Classing Floating Offshore Wind Turbine Installations are relatively new and few if any floating wind turbines have yet experienced the prescribed design extreme environmental conditions. Only a few pilot floating turbines have been deployed in Europe and Japan. These turbines have been designed for long return period storm events and are not likely to see their extreme design conditions during early deployment periods because of the low probability of occurrence. This paper presents data collected for an intermediate scale floating semi‐submersible turbine intentionally placed offshore Maine in a carefully selected site that subjects the prototype to scale extreme conditions on a frequent basis. This prototype, called VolturnUS 1:8, was the first grid‐connected offshore wind turbine in the Americas, and is a 1:8 scale model of a 6 MW prototype. The test site produces with a high probability 1:8 scale wave environments, and a commercial turbine has been selected so that the wind environment/rotor combination produces 1:8‐scale aerodynamic loads appropriate for the site wave environment. In the winter of 2013–2014, this prototype has seen the equivalent of 50 year to 500 year return period storms exercising it to the limits prescribed by design standards, offering a unique look at the behavior of a floating turbine subjected to extreme design conditions. Performance data are provided and compared to full‐scale predicted values from numerical models. There are two objectives in presenting this data and associated analysis: (i) validate numerical aeroelastic hydrodynamic coupled models and (ii) investigate the performance of a near full‐scale floating wind turbine in a real offshore environment that closely matches the prescribed design conditions from the ABS Guide. Copyright © 2015 John Wiley & Sons, Ltd.     

大型风电机组功率曲线的分析与修正

讨论了风电机组不同情况下的功率曲线定义,分析了功率曲线绘制过程中的风速处理方法,可以适用于绘制风力发电机组静、动态功率曲线;讨论了影响机组功率曲线的各种因素,并给出了影响因子,使得根据功率曲线进行风场发电量的计算可以取得更可靠的结果。     

Control of wind generator associated to a flywheel energy storage system

In this paper, a doubly fed variable speed wind induction generator connected to the grid associated to a flywheel energy storage system (FESS) is investigated. The dynamic behaviour of a wind generator, including the models of the wind turbine (aerodynamic), the doubly fed induction generator (DFIG), a ac/ac direct converter, the converter control (algorithm of VENTURINI) and the power control of this system, is studied. Also investigated is a control method of the FESS system, which consists of the classical squirrel-cage induction machine supplied off the variable speed wind generator (VSWG) through a rectifier–inverter cascade arrangement. Simulation results obtained on the basis of the dynamic models of the wind generator are presented, for different operating points, to demonstrate the performance of the proposed system.     

Validation of a hybrid modeling approach to floating wind turbine basin testing

Hybrid modeling combining physical tests and numerical simulations in real time opens new opportunities in floating wind turbine research. Wave basin testing is an important validation step for floating support structure design, but current methods are limited by scaling problems in the aerodynamic loadings. Applying wind turbine loads with an actuation system controlled by a simulation that responds to the basin test offers a way to avoid scaling problems and reduce cost barriers for floating wind turbine design validation in realistic coupled conditions. In this work, a cable‐based hybrid coupling approach is developed and implemented for 1:50‐scale wave basin tests with the DeepCwind semisubmersible floating wind turbine. Tests are run with thrust loads provided by a numerical wind turbine model. Matching tests are run with physical wind loads using an above‐basin wind maker. When the numerical submodel is set to match the aerodynamic performance of the physical scaled wind turbine, the results show good agreement with purely physical wind‐wave tests, validating the hybrid model approach. Further hybrid model tests with simulated true‐to‐scale dynamic thrust loads and wind turbulence show noticeable differences and demonstrate the value of a hybrid model approach for improving the true‐to‐scale realism of floating wind turbine basin tests.     

Errors and uncertainties associated with missing wind data and short records

A near‐complete 4 year data set of 10 min average 80 m wind speeds is used to examine the impact of missing data on monthly and yearly estimates of mean wind speed and energy production from a generic wind turbine. Missing data is a source of uncertainty in wind energy resource assessment studies. Quantifying that uncertainty can improve the reliability of P90 and related wind farm energy production estimates. An empirical relationship between missing data percentage and relative uncertainty in monthly mean wind speed is derived. Relationships between uncertainties in monthly average wind speed and uncertainties in monthly energy production are also explored. In many cases with monthly data losses of 10% or less the contribution to the overall uncertainty in annual energy production will be small (<1%), but with substantial losses in cold winters, typically caused by icing; the uncertainties can become more significant. The data set is also used to indicate uncertainties associated with short data periods. Annual average wind speed estimates based on less than a complete year's data also add significant uncertainty to wind resource assessments. Copyright © 2013 John Wiley & Sons, Ltd.     

Technoeconomic study for the optimization of turbine size and wind farm layouts

A technoeconomic analysis and optimization of wind turbine size and layout are performed using WAsP software. A case study of a 100‐MW wind farm located in Egypt is considered. Wind atlas for Egypt was used as the input data of the WAsP software. Two turbine models of powers 52 and 80 MW are considered for this project. The wind turbine size and distributions are selected based on the technoeconomic optimization, namely minimum wake effect, maximum annual energy production (AEP) rate, optimum cash flow, and payback period. The future worth method is adopted in economic comparison between the two alternatives, and the cash flow diagram provided the payback period and future worth after the lifetime of the plant. The results showed that (1) the AEP dramatically decreases for a wind farm area less than 15 km²; (2) the turbine spacing, spacing‐to‐diameter ratio, and the setback distances decrease and the wind turbine density and wake losses increase with decreasing the wind turbines size; (3) the total net AEP using G52 is lower than that of using G80 by about 16%; (4) the technoeconomic analysis recommended using G80 as it has higher profit than those of G52 by about $20 million.     

Atmospheric stability‐dependent infinite wind‐farm models and the wake‐decay coefficient

We extend the infinite wind‐farm boundary‐layer (IWFBL) model of Frandsen to take into account atmospheric static stability effects. This extended model is compared with the IWFBL model of Emeis and to the Park wake model used in Wind Atlas Analysis and Application Program (WAsP), which is computed for an infinite wind farm. The models show similar behavior for the wind‐speed reduction when accounting for a number of surface roughness lengths, turbine to turbine separations and wind speeds under neutral conditions. For a wide range of atmospheric stability and surface roughness length values, the extended IWFBL model of Frandsen shows a much higher wind‐speed reduction dependency on atmospheric stability than on roughness length (roughness has been generally thought to have a major effect on the wind‐speed reduction). We further adjust the wake‐decay coefficient of the Park wake model for an infinite wind farm to match the wind‐speed reduction estimated by the extended IWFBL model of Frandsen for different roughness lengths, turbine to turbine separations and atmospheric stability conditions. It is found that the WAsP‐recommended values for the wake‐decay coefficient of the Park wake model are (i) larger than the adjusted values for a wide range of neutral to stable atmospheric stability conditions, a number of roughness lengths and turbine separations lower than ～ 10 rotor diameters and (ii) too large compared with those obtained by a semiempirical formulation (relating the ratio of the friction to the hub‐height free velocity) for all types of roughness and atmospheric stability conditions. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

大型风力发电场选址与风力发电机优化匹配

从风能利用和风电成本两个角度出发,推导出风电场选址与风力机优化选型的目标函数,提出将风力机容量系数作为风电场选址与风力机选型的判据,同时给出了基于风速分布特性的风力机容量系数计算方法。通过我国云南省的13个实际风速观测点和国内外25种风力机代表机型的计算,给出了这些观测点的开发顺序及优化配置的风力机机型,并简要分析了影响风力机容量系数的主要因素。实践表明,这种方法物理意义明确,计算快捷方便,节省设计时间和设计工作量。     

基于正交化的混合式平台漂浮式风电场平台动态响应研究

为研究混合式平台漂浮式风电场平台动态响应,分别建立基于Spar和Barge平台的漂浮式风力机整机模型,采用链接悬链线和固定悬链线将其链接以建立2×2阵列漂浮式风电场。采用叶素动量理论计算风载荷,通过辐射/绕射理论求解波浪载荷,采用水动力学软件AQWA研究风波载荷作用下漂浮式风电场平台的动态响应。针对Spar和Barge平台尺度大小不同导致系泊系统不对称引起的Spar平台横摇和艏摇响应较大问题,提出"依照尺度最大平台正交布置链接悬链线"的漂浮式风电场系泊系统布置准则。为验证所提出的系泊系统布置准则的可行性,对比研究系泊系统正交化前后漂浮式风电场平台的动态响应。结果表明,在极限海况下,系泊系统的正交化布置可减小Spar平台横荡响应,但一定程度会增加纵荡响应;而系泊系统正交化与否对漂浮式风电场平台垂荡、纵摇响应和机舱加速度影响较小。此外,正交化布置的系泊系统可显著减小Spar平台横摇和艏摇响应、Barge平台艏摇响应,而Barge平台横摇响应几乎不受影响。