An experimental investigation on the wake interferences among wind turbines sited in aligned and staggered wind farms

An experimental investigation was conducted for a better understanding of the wake interferences among wind turbines sited in wind farms with different turbine layout designs. Two different types of inflows were generated in an atmospheric boundary layer wind tunnel to simulate the different incoming surface winds over typical onshore and offshore wind farms. In addition to quantifying the power outputs and dynamic wind loads acting on the model turbines, the characteristics of the wake flows inside the wind farms were also examined quantitatively. After adding turbines staggered between the first 2 rows of an aligned wind farm to increase the turbine number density in the wind farm, the added staggered turbines did not show a significant effect on the aeromechanical performance of the downstream turbines for the offshore case. However, for the onshore case, while the upstream staggered turbines have a beneficial effect on the power outputs of the downstream turbines, the fatigue loads acting on the downstream turbines were also found to increase considerably due to the wake effects induced by the upstream turbines. With the same turbine number density and same inflow characteristics, the wind turbines were found to be able to generate much more power when they are arranged in a staggered layout than those in an aligned layout. In addition, the characteristics of the dynamic wind loads acting on the wind turbines sited in the aligned layout, including the fluctuation amplitudes and power spectrum, were found to be significantly different from those with staggered layout.     

Variable‐sized wind turbines are a possibility for wind farm optimization

The potential benefits associated with harnessing available momentum and reducing turbulence levels in a wind farm composed of wind turbines of alternating size are investigated through wind tunnel experiments. A variable size turbine array composed of 3 by 8 model wind turbines is placed in a boundary layer flow developed over both a smooth and rough surfaces under neutrally stratified thermal conditions. Cross‐wire anemometry is used to capture high resolution and simultaneous measurements of the streamwise and vertical velocity components at various locations along the central plane of the wind farm. A laser tachometer is employed to obtain the instantaneous angular velocity of various turbines. The results suggest that wind turbine size heterogeneity in a wind farm introduces distinctive flow interactions not possible in its homogeneous counterpart. In particular, reduced levels of turbulence around the wind turbine rotors may have positive effects on turbulent loading. The turbines also appear to perform quite uniformly along the entire wind farm, whereas surface roughness impacts the velocity recovery and the spectral content of the turbulent flow within the wind farm. Copyright © 2013 John Wiley & Sons, Ltd.     

A comparison of methods for assessing power output in non‐uniform onshore wind farms

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.     

Uncertainty quantification of infinite aligned wind farm performance using non‐intrusive polynomial chaos and a distributed roughness model

Uncertainty of wind farm parameters can have a significant effect on wind farm power output. Knowledge of the uncertainty‐produced stochastic distribution of the entire wind farm power output and the corresponding uncertainty propagation mechanisms is very important for evaluating the uncertainty effects on the wind farm performance during wind farm planning stage and providing insights on improving the performance of the existing wind farms. In this work, the propagation of uncertainties from surface roughness and induction factor in infinite aligned wind farms modeled by a modified distributed roughness model is investigated using non‐intrusive polynomial chaos. Stochastic analysis of surface roughness indicates that 30% uncertainty can propagate such that there is up a 8% uncertainty in the power output of the wind farm by affecting the uncertainty in the position of the individual wind turbines in the vertical boundary layer profile and uncertainty in vertical momentum fluxes which replenish energy in the wake in large wind farms. Induction factor uncertainty of the wind turbines can also have a significant effect on power output. Not only does its uncertainty substantially affect the vertical boundary layer profile, but the uncertainty in turbine wake growth which affects how neighboring turbine wakes interact. We found that optimal power output in terms of reduction of uncertainty closely correlates with the Betz limit and is dependent on the mean induction factor. Copyright © 2016 John Wiley & Sons, Ltd.     

Dependence of optimal wind turbine spacing on wind farm length

Recent large eddy simulations have led to improved parameterizations of the effective roughness height of wind farms. This effective roughness height can be used to predict the wind velocity at hub‐height as function of the geometric mean of the spanwise and streamwise turbine spacings and the turbine loading factors. Recently, Meyers and Meneveau used these parameterizations to make predictions for the optimal wind turbine spacing in infinitely large wind farms. They found that for a realistic cost ratio between the turbines and the used land surface, the optimal turbine spacing may be considerably larger than that used in conventional wind farms. Here, we extend this analysis by taking the length of the wind farm, i.e. the number of rows in the downstream direction into account and show that the optimal turbine spacing strongly depends on the wind farm length. For small to moderately sized wind farms, the model predictions are consistent with spacings found in operational wind farms. For much larger wind farms, the extended optimal spacing found for infinite wind farms is confirmed. Copyright © 2015 John Wiley & Sons, Ltd.     

Cost performance and risk in the construction of offshore and onshore wind farms

This article investigates the risk of cost overruns and underruns occurring in the construction of 51 onshore and offshore wind farms commissioned between 2000 and 2015 in 13 countries. In total, these projects required about $39 billion in investment and reached about 11 GW of installed capacity. We use this original dataset to test six hypotheses about construction cost overruns related to (i) technological learning, (ii) fiscal control, (iii) economies of scale, (iv) configuration, (v) regulation and markets and (vi) manufacturing experience. We find that across the entire dataset, the mean cost escalation per project is 6.5% or about $63 million per windfarm, although 20 projects within the sample (39%) did not exhibit cost overruns. The majority of onshore wind farms exhibit cost underruns while for offshore wind farms the results have a larger spread. Interestingly, no significant relationship exists between the size (in total MW or per individual turbine capacity) of a windfarm and the severity of a cost overrun. Nonetheless, there is an indication that the risk increases for larger wind farms at greater distances offshore using new types of turbines and foundations. Overall, the mean cost escalation for onshore projects is 1.7% and 9.6% for offshore projects, amounts much lower than those for other energy infrastructure. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Exploring the gap between ‘best knowledge’ and ‘best practice’ in boundary layer meteorology for offshore wind energy

Onshore wind turbine technology is moving offshore, and the offshore wind industry tends to use larger turbines than those used over land. This calls for an improved understanding of the marine boundary layer. The standards used in the design of offshore wind turbines, particularly the rotor–nacelle assembly, are similar to those used for onshore wind turbines. As a result, simplifications regarding the marine boundary layer are made. Atmospheric stability considerations and wave effects, including the dynamic sea surface roughness, are two major factors affecting flow over sea versus land. Neutral stratification and a flat, smooth sea surface are routinely used as assumptions in wind energy calculations. Newly published literature in the field reveals that the assumption of a neutral stratification is not necessarily a conservative approach. Design tests based on neutral stratification give the lowest fatigue damage on the rotors. Turbulence, heat exchange and momentum transfer depend on the sea state, but this is usually ignored, and the sea surface is thought of as level and smooth. Field experiments and numerical simulations show that during swell conditions, the wind profile will no longer exhibit a logarithmic shape, and the surface drag relies on the sea state. Stratification and sea state are parameters that can be accounted for, and they should therefore be considered in design calculations, energy assessments and power output predictions. Copyright © 2012 John Wiley & Sons, Ltd.     

海上风电场智慧运维管理系统

[目的]针对海上风电场运维安全管理,提出了海上风电场智慧运维管理系统.[方法]通过海上风电智慧调度系统、海上风电雷达多源跟踪及边界警示系统、海上风电场风机平台作业监管系统,搭建出海上风电场智慧运维管理系统.[结果]通过陆上集控中心的海上风电智慧调度系统,实现人员的安全管理以及船舶调度.通过海上风电雷达多源跟踪及边界警示...     

Availability,operation and maintenance costs of offshore wind turbines with different drive train configurations

Different configurations of gearbox, generator and power converter exist for offshore wind turbines. This paper investigated the performance of four prominent drive train configurations over a range of sites distinguished by their distance to shore. Failure rate data from onshore and offshore wind turbine populations was used where available or systematically estimated where no data was available. This was inputted along with repair resource requirements to an offshore accessibility and operation and maintenance model to calculate availability and operation and maintenance costs for a baseline wind farm consisting of 100 turbines. The results predicted that turbines with a permanent magnet generator and a fully rated power converter will have a higher availability and lower operation and maintenance costs than turbines with doubly fed induction generators. This held true for all sites in this analysis. It was also predicted that in turbines with a permanent magnet generator, the direct drive configuration has the highest availability and lowest operation and maintenance costs followed by the turbines with two‐stage and three‐stage gearboxes. Copyright © 2016 John Wiley & Sons, Ltd.     

Mesoscale modeling of offshore wind turbine wakes at the wind farm resolving scale: a composite‐based analysis with the Weather Research and Forecasting model over Horns Rev

The use of mesoscale modeling to reproduce the power deficits associated with wind turbine wakes in an offshore environment is analyzed. The study is based on multiyear (3 years) observational and modeling results at the Horns Rev wind farm. The simulations are performed with the Weather Research and Forecasting mesoscale model configured at a high horizontal resolution of 333 m over Horns Rev. The wind turbines are represented as an elevated momentum sink and a source of turbulent kinetic energy. Composites with different atmospheric conditions are extracted from both the observed and simulated datasets in order to inspect the ability of the model to reproduce the power deficit in a wide range of atmospheric conditions. Results indicate that mesoscale models such as Weather Research and Forecasting are able to qualitatively reproduce the power deficit at the wind farm scale. Some specific differences are identified. Mesoscale modeling is therefore a suitable framework to analyze potential downstream effects associated with offshore wind farms. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimization of cable layout designs for large offshore wind farms

Installation of a wind farm exposes several problems such as site selection, placement of wind turbines in the site, and designing of cable infrastructure within the farm. The latter problem, called cable layout design, is the determination of cable connections among turbines and one or more transmitters such that energies generated by turbines will be sent through the cable routes, and eventually gathered at the transmitter(s). This problem is especially important for offshore wind farms where the featured and expensive cables are used. The main objective of the present study is to address the cable layout design problem of offshore wind farms to reduce cable costs in the design using optimization-based approaches. The problem, firstly, is modelled as a mixed integer linear program (MIP) under a set of real-life constraints such as different cable and transmitter types and non-crossing connections between the turbines. Then, a novel mathematical model, which is a modification of the MIP model by imposing several heuristic rules, is proposed to solve the layout problem of large offshore wind farms. Experiments on a set of small- and moderate-sized test instances reveal that the heuristic model, MIP_H, reduces the computer time nearly 55% compared to that of MIP model while the average cable costs generated by the models are close to each other. MIP_H, besides its efficiency, provides more cost-effective layouts compared to MIP model for large-sized real-life examples. Additionally, a comparative study on MIP_H and existing methods in the literature shows that MIP_H is able to solve all instances of the real-life examples providing less cable costs in average.     

Wake impacts on downstream wind turbine performance and yaw alignment

Aerodynamic wake interaction between commercial scale wind turbines can be a significant source of power losses and increased fatigue loads across a wind farm. Significant research has been dedicated to the study of wind turbine wakes and wake model development. This paper profiles influential wake regions for an onshore wind farm using 6 months of recorded SCADA (supervisory control and data acquisition) data. An average wind velocity deficit of over 30% was observed corresponding to power coefficient losses of 0.2 in the wake region. Wind speed fluctuations are also quantified for an array of turbines, inferring an increase in turbulence within the wake region. A study of yaw data within the array showed turbine nacelle misalignment under a range of downstream wake angles, indicating a characteristic of wind turbine behaviour not generally considered in wake studies. The turbines yaw independently in order to capture the increased wind speeds present due to the lateral influx of turbulent wind, contrary to many experimental and simulation methods found in the literature. Improvements are suggested for wind farm control strategies that may improve farm‐wide power output. Additionally, possible causes for wind farm wake model overestimation of wake losses are proposed.Copyright © 2012 John Wiley & Sons, Ltd.     

Dynamic models of wind farms with fixed speed wind turbines

The increasing wind power penetration on power systems requires the development of adequate wind farms models for representing the dynamic behaviour of wind farms on power systems. The behaviour of a wind farm can be represented by a detailed model including the modelling of all wind turbines and the wind farm electrical network. But this detailed model presents a high order model if a wind farm with high number of wind turbines is modelled and therefore the simulation time is long. The development of equivalent wind farm models enables the model order and the computation time to be reduced when the impact of wind farms on power systems is studied. In this paper, equivalent models of wind farms with fixed speed wind turbines are proposed by aggregating wind turbines into an equivalent wind turbine that operates on an equivalent wind farm electrical network. Two equivalent wind turbines have been developed: one for aggregated wind turbines with similar winds, and another for aggregated wind turbines under any incoming wind, even with different incoming winds.The proposed equivalent models provide high accuracy for representing the dynamic response of wind farm on power system simulations with an important reduction of model order and simulation time compare to that of the complete wind farm modelled by the detailed model.     

Power loss in the upper cut‐out wind speed interval

Time series of mean wind speeds at several sites in Denmark have been used to estimate the power loss for wind turbines in the wind speed interval from where the operation has to stop at high winds to where a lower wind speed allows the operation to resume. For inland wind turbines the fractional loss is less than 0·25%. For offshore wind turbines it may be as high as about 1·5%. To facilitate the estimation of ‘dead zone’ power loss for offshore wind turbines, an engineering model for the sea surface state has been developed on the basis of a generalization of Charnock's roughness model and the geostrophic drag law. This model predicts the surface friction velocity and the surface roughness as functions of the geostrophic wind speed and the length of the water fetch. Copyright © 2004 John Wiley & Sons, Ltd.     

Risk analysis of maintenance ship collisions with offshore wind turbines

A large number of offshore wind farms are planned to be built in remote deep-sea areas over the next five years. Though offshore wind sites are often located away from commercial ship traffic, the increased demand for repair or replacement services leads to high traffic densities of “maintenance ships”. To date, the risk analysis of collision between maintenance ship vessels and offshore wind turbines has received very little attention. In this paper, we propose a methodology to evaluate and prioritise the collision risks associated with various kinds of ships used for carrying out maintenance tasks on different subassemblies of wind turbines in an offshore wind farm. It is also studied how the risks of ship collision with wind turbines are distributed between two main types of maintenance tasks, namely corrective and preventative. The proposed model is tested on an offshore wind turbine with seventeen components requiring five kinds of ships to perform the maintenance tasks. Our results indicate that collision risks are mostly associated with maintenance of few components of the wind turbine and in particular, those undergoing a corrective maintenance (replacement). Finally, several mitigation strategies are introduced to minimise the risk of maintenance ship collisions with offshore wind turbines.     

某近海风电场风机基础选型设计

目的  自2022年起,海上风电的国家补贴将全面退出。海上风电机组基础是风电机组的支撑结构,对海上风电场的安全运行起着至关重要的作用。在平价上网、“30·60”双碳目标和国家“十四五”能源规划等政策的指导下,合理地选择、设计海上风电机组基础,是海上风电场降本增效的有效手段。 方法  文章以某近海风电场风机基础选型设计为例,综合国内海上风电场的建设经验,进行基础型式比选;首先选择单桩基础、导管架基础和高桩承台基础3种基础型式进行初选,然后结合该近海风电场的海洋水文和地质条件,分析不同风机基础型式的适用水深及优缺点,从结构安全性、施工可行性、工期及工程经济性等方面进行了综合比选。 结果  研究表明：风机基础型式的选择与水深、土层地质条件、风电机组固有频率、施工安装设备能力、施工工期、工程造价等几个因素有关。单桩基础结构型式优良、施工可行、工期最短、经济性最优,优势明显。 结论  推荐该近海风电场风机基础采用单桩基础方案。     

海上相邻风电场间的“尾流效应”实例分析

目的  研究海上相邻风电场间的“尾流效应”对发电损失的影响。 方法  利用海上风电场实际运行SCADA数据结合激光雷达同期实测测风数据,基于不同的风向扇区范围和风电场实际排布进行尾流效应场景分类,开展实际运行相邻风电场间（20D以上间距）的真实尾流电量损失分析工作。 结果  结果表明：对于规则排布的海上大型风电场,基于实际运行SCADA数据,对各机组发电量进行归一化,可以较好地反映海上风能资源分布特征及各机组发电能力的差异;高度集中的单一扇区条件下,处于下风向的相邻风电场受上风向相邻场区的“尾流效应”影响明显,发电产能较自由流降幅明显;相邻风场间随着缓冲带距离的增加,下风向场区机组尾流电量衰减比随之降低,缓冲带需达到一定的距离,对于风速的恢复有明显的作用,发电产能才能够有所提升;本案例不同场景下,缓冲带距离在23D～44D之间,尾流损失电量降幅在27%～4%之间。 结论  基于相邻风电场实际运行数据开展尾流分析可为后续海上大型风电基地规划设计和机组排布优化设计提供指导。     

Greenhouse gas emissions from electricity generated by offshore wind farms

For wind power generation offshore sites offer significantly better wind conditions compared to onshore. At the same time, the demand for raw materials and therefore the related environmental impacts increase due to technically more demanding wind energy converters and additional components (e.g. substructure) for the balance of plant. Additionally, due to environmental concerns offshore wind farms will be sited farshore (i.e. in deep water) in the future having a significant impact on the operation and maintenance efforts (O&M). Against this background the goal of this analysis is an assessment of the specific GHG (greenhouse gas) emissions as a function of the site conditions, the wind mill technology and the O&M necessities. Therefore, a representative offshore wind farm is defined and subjected to a detailed LCA (life cycle assessment). Based on parameter variations and modifications within the technical and logistical system, promising configurations regarding GHG emissions are determined for different site conditions. Results show, that all parameters related to the energy yield have a distinctive impact on the specific GHG emissions, whereas the distance to shore and the water depth affect the results marginally. By utilizing the given improvement potentials GHG emissions of electricity from offshore wind farms are comparable to those achieved onshore.     

Windstorm risk assessment for offshore wind farms in the North Sea

The North Sea is becoming increasingly attractive to wind energy developers and investors, with 38 wind farms belonging to five different countries and representing over€35 billion of assets. Concerns about offshore wind turbines being damaged by extreme windstorms pose a challenge to insurers, investors and regulators. Catastrophe modeling can adequately quantify the risk. In this study, a Monte Carlo simulation approach is used to assess the number of turbines that buckle using maximum wind speeds reaching each wind farm. Damage assessment is undertaken for each wind farm using a log‐logistic damage function and a left‐truncated Weibull distribution. The risk to offshore wind power in the North Sea is calculated using an exceedance probability (EP) curve for the portfolio of wind farms. The European Union Solvency II directive requires insurance companies to hold sufficient capital to guard against insolvency. The solvency capital requirement (SCR) is based on a value‐at‐risk measure calibrated to a 99.5% confidence level over a 1‐year time horizon. The SCR is estimated at €0.049 billion in the case of yawing turbines. Simulations are repeated for different climate change scenarios. If wind speeds grow by 5% and the frequency of storms increases by 40%, the SCR is seen to rise substantially to €0.264 billion. Relative to the total value of assets, the SCR is 0.14% compared with 0.08% for European property, confirming that these wind farm assets represent a relatively high risk. Furthermore, climate change could increase the relative SCR to levels as high as 0.75%.