Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil

Wind is strong and steady over the ocean, but on-site marine meteorological data are sparse for evaluation of oceanic wind power. Here, we draw on meteorological station, satellite data (QuikSCAT), and both theoretical and practical measures of wind turbine performance. The meteorological stations measure directly at high time resolution but low spacial resolution, and provide validation and adjustment of the satellite data. The satellite data provide near-complete spacial coverage at lower time resolution. For the southern coast of Brazil, we use both data sets to evaluate the location, seasonal timing, and availability of the wind power resource. Then, using bathymetry and the properties of current wind-electric technology, we develop maps of wind speed, wind power density, and practical turbine output in power units (MW). In the shallower waters of south Brazil, the most favorable conditions are along the coast between 28°S and 33°S. In just this one coastal area, we find a total resource of 102 GW average electrical production, approximately equal to the electric demand of the entire country.     

Dynamic characteristics and enhanced performance of a novel wind turbine rotor analyzed via experiments and numerical simulation

The enormous demand for large wind turbine rotors has led to a need to develop high‐performance and reliable wind turbine rotors. The flexibility of the huge blade was a challenge in creating a balanced design with regard to dynamic behavior, mass, and power output. To enhance the wind turbine rotor, a newly designed wind turbine system with a supporting rod and damper was proposed and investigated. A scaled blade was experimentally tested, with the results indicating an increase in both frequency and damping of the system. Through the use of a self‐coded numerical model, the correlations between the design constraints and the dynamic behavior, tip displacement, and additional mass of the rotor were demonstrated. This showed that the novel rotor has some preferable characteristics in both static and dynamic aspects. In particular, this blade is stiffer and has a smaller tip displacement compared with a traditional cantilevered blade. These characteristics enabled the effective application of the novel rotor to a 5‐MW wind turbine to achieve a 15.16% power output increase based on the blade element momentum theory with Prandtl correction, as well as 5.1% mass savings. Copyright © 2016 John Wiley & Sons, Ltd.     

Power correlation for vertical axis wind turbines with varying geometries

In this paper, a new predictive model that can forecast the performance of a vertical axis wind turbine (VAWT) is presented. The new model includes four primary variables (rotor velocity, wind velocity, air density, and turbine power output) as well as five geometrical variables (rotor radius, turbine height, turbine width, stator spacing, and stator angle). These variables are reduced to include the power coefficient (C_p) and tip speed ratio (TSR). A power coefficient correlation for a novel VAWT (called a Zephyr Vertical axis Wind Turbine (ZVWT)) is developed. The turbine is an adaptation of the Savonius design. The new correlation can predict the turbine's performance for altered stator geometry and varying operating conditions. Numerical simulations with a rotating reference frame are used to predict the operating performance for various turbine geometries. The case study includes 16 different geometries for three different wind directions. The resulting 48 data points provide detailed insight into the turbine performance to develop a general correlation. The model was able to predict the power coefficient with changes in TSR, rotor length, stator spacing, and stator angle, to within 4.4% of the numerical prediction. Furthermore, the power coefficient was predicted with changes in rotor length, stator spacing, and stator angle, to within 3.0% of the numerical simulations. This correlation provides a useful new design tool for improving the ZVWT in the specific conditions and operating requirements specific to this type of wind turbine. Also, the new model can be extended to other conditions that include different VAWT designs. Copyright © 2010 John Wiley & Sons, Ltd.     

Sensitivity of southern California wind energy to turbine characteristics

Using output from a high‐resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut‐in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut‐out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd.     

雾霾之后的反思

新年过后的第二个周末,浓重的雾霾已在全国多个城市肆虐,这让人们的心情变得糟糕。数据显示,截至1月13日零时,全国有33个城市的部分监测点PM2.5浓度超过300微克/立方米,个别城市出现PM2.5"爆表",比如北京的PM2.5浓度最高达到950微克/立方米。环保专家称,如此严重的空气质量污染,可以说已近人类所能承受的极限。于是,人们看到了政府有关方面发布的紧急预案,比如通知市民减少户外活动,要求学校停止户外体育锻炼,这体现了政府的责任意识。但我们是满足于制定完美的灾情应对预案,还是谋求从根本上消除灾难?     

A flywheel in a wind turbine rotor for inertia control

In this paper, a flywheel energy storage that is an integral part of a wind turbine rotor is proposed. The rotor blades of a wind turbine are equipped with internal weights, which increase the inertia of the rotor. The inertia of this flywheel can be controlled by varying the position of the weights, i.e. by positioning them closer to the center of rotation (closer to the hub) or closer to the tip of the blades. The simulation model used in this study is introduced briefly. The equation system of the flywheel is set up. Finally, simulations of different scenarios show the performance of this controllable flywheel. The conclusion is that the proposed system can mitigate transients in the power output of wind turbines. Hence, it can support the frequency control in a power system by contributing to the power system inertia. © 2014 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

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.     

Detecting,categorizing and forecasting large ramps in wind farm power output using meteorological observations and WPPT

The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind farm. This article analyses the general performance of WPPT as well as its performance during large ramps (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real‐time wind power observations to make hourly forecasts of the wind farm power output. The general performances of MesoLAPS and WPPT are evaluated over 1 year using the root mean square error (RMSE). The errors are significantly lower than for basic benchmark forecasts but higher than for many other WPPT installations, where the site conditions are not as complicated as Woolnorth Bluff Point. Large ramps are considered critical events for a wind power forecast for energy trading as well as managing power system security. A methodology is developed to detect large ramp events in the wind farm power data. Forty‐one large ramp events are detected over 1 year and these are categorized according to their predictability by MesoLAPS, the mechanical behaviour of the wind turbine, the power change observed on the grid and the source weather event. During these events, MesoLAPS and WPPT are found to give an RMSE only roughly equivalent to just predicting the mean (climatology forecast). Copyright © 2007 John Wiley & Sons, Ltd.     

Redefining the design objectives of large offshore wind turbine rotors

Wind turbine rotors are normally designed such that rotor power coefficient is maximized. Much of this methodology has been inherited from the aviation industry. This paper points out that designing machines for maximum rotor aerodynamic efficiency does not necessarily lead to a lower levelized cost of energy. The argument sits on the premise that levelized cost of energy is strongly influenced by machine capital expenditure (CAPEX) and annual energy production (AEP). We therefore assume that the true design objective is to minimize the CAPEX/AEP ratio. The basis of an alternative design path is presented, which centres on the minimization of total volume of structural material in the wind turbine. This is done whilst maintaining a given rated power. This alternative methodology requires the removal of conventional pre‐set design variables and assumptions which relate to the maximization of rotor power coefficient. We examine how changing chord length, axial induction factor and aerofoil lift coefficient affect material volume in the blade. Following this, we use a custom‐made blade element momentum programme to explore the relative CAPEX of machines with varying design axial induction factor and varying lift coefficient. This relative cost is calibrated to the 5 MW National Renewable Energy Laboratory offshore reference turbine. The effects on the rotor, drivetrain and tower are considered. For a 5 MW offshore machine, it is shown that an overall CAPEX/AEP reduction of over 2% can be achieved by using a low‐induction rotor with blades possessing aerofoils operating at non‐peak lift to drag ratios. This economy is delivered notwithstanding a 2.3% drop in design rotor power coefficient. Copyright © 2014 John Wiley & Sons, Ltd.     

The concept of a smart wind turbine system

A smart wind turbine concept with variable length blades and an innovative hybrid mechanical-electrical power conversion system was analyzed. The variable length blade concept uses the idea of extending the turbine blades when wind speeds fall below rated level, hence increasing the swept area, and thus maintaining a relatively high power output. It is shown for a typical site, that the annual energy output of such a wind turbine that could double its blade length, could be twice that of a corresponding turbine with fixed length blades. From a cost analysis, it is shown that the concept would be feasible if the cost of the rotor could be kept less than 4.3 times the cost of a standard rotor with fixed length blades. Given the variable length blade turbine system exhibits a more-or-less linear maximum power curve, as opposed to a non-linear curve for the standard turbine, an innovative hybrid mechanical-electrical power conversion system was proposed and tested proving the feasibility of the concept.     

Large‐eddy simulation of turbulent flow past wind turbines/farms: the Virtual Wind Simulator (VWiS)

A large‐eddy simulation framework, dubbed as the Virtual Wind Simulator (VWiS), for simulating turbulent flow over wind turbines and wind farms in complex terrain is developed and validated. The wind turbines are parameterized using the actuator line model. The complex terrain is represented by the curvilinear immersed boundary method. The predictive capability of the present method is evaluated by simulating two available wind tunnel experimental cases: the flow over a stand‐alone turbine and an aligned wind turbine array. Systematic grid refinement studies are carried out, for both single turbine and multi‐turbine array cases, and the accuracy of the computed results is assessed through detailed comparisons with wind tunnel experiments. The model is further applied to simulate the flow over an operational utility‐scale wind farm. The inflow velocities for this case are interpolated from a mesoscale simulation using a Weather Research and Forecasting (WRF) model with and without adding synthetic turbulence to the WRF‐computed velocity fields. Improvements on power predictions are obtained when synthetic turbulence is added at the inlet. Finally the VWiS is applied to simulate a yet undeveloped wind farm at a complex terrain site where wind resource measurements have already been obtained. Good agreement with field measurements is obtained in terms of the time‐averaged streamwise velocity profiles. To demonstrate the ability of the model to simulate the interactions of terrain‐induced turbulence with wind turbines, eight hypothetical turbines are placed in this area. The computed extracted power underscores the significant effect of site‐specific topography on turbine performance. Copyright © 2014 John Wiley & Sons, Ltd.     

Rotor dynamics correlation for maximum power and transient control of wind turbines

In this paper, a new rotor dynamics model is developed for transient power output from a horizontal axis wind turbine. In addition to the standard maximum kinetic energy of the wind, the model incorporates rotor velocity and rotational acceleration to enhance the control techniques that convert mechanical to electrical energy via shaft rotation. With current methods, the wind kinetic energy is generally the primary parameter that establishes maximum power output. By relating this wind energy to the rotor dynamics, electrical systems can have a more useful upper bound for the rotor control strategy. The new model predicts the rotor velocity for various turbine configurations, operating over a range of wind conditions. The predicted results show that the same power output is obtained as the standard kinetic energy approach, but with significant additional opportunity to better control the rotor dynamics. Copyright © 2009 John Wiley & Sons, Ltd.     

A new semi-empirical wind turbine capacity factor for maximizing annual electricity and hydrogen production

The capacity factor is an important wind turbine parameter which is ratio of average output electrical power to rated electrical power of the wind turbine. Another main factor, the AEP, the annual energy production, can be determined using wind characteristics and wind turbine performance. Lower rated power may lead to higher capacity factor but will reduce the AEP. Therefore, it is important to consider simultaneously both the capacity factor and the AEP in design or selecting a wind turbine. In this work, a new semi-empirical secondary capacity factor is introduced for determining a rated wind speed at which yearly energy and hydrogen production obtain a maximum value. This capacity factor is expressed as ratio of the AEP for wind turbine to yearly wind energy delivered by mean wind speed at the rotor swept area. The methodology is demonstrated using the empirical efficiency curve of Vestas-80 2 MW turbine and the Weibull probability density function. Simultaneous use of the primary and the secondary capacity factors are discussed for maximizing electrical energy and hence hydrogen production for different wind classes and economic feasibility are scrutinized in several wind stations in Kuwait.     

基于SCADA运行数据的风电机组发电性能劣化监测研究

风电机组的发电效率和发电性能对风电场的运行水平和经济效益有重要影响。文章采用风电机组SCADA运行数据对机组发电性能劣化进行监测。首先,采用偏最小二乘方法确定对风电机组发电功率有密切影响的多个变量;然后,采用高斯过程回归方法建立反映机组发电性能的功率曲线模型,有效提高建模精度;在监测阶段,引入指数加权移动平均值控制图(EWMA)分析功率曲线模型的功率预测残差,及时准确地发出风电机组发电性能劣化预警;最后,以某风电机组叶轮转速传感器故障导致的发电性能劣化实例,验证了该方法的有效性。     

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

Wind energy uptake in South Africa is significantly increasing both at the micro‐ and macro‐level and the possibility of embedded generation cannot be undermined considering the state of electricity supply in the country. This study identifies a wind hotspot site in the Eastern Cape province, performs an in silico deployment of three utility‐scale wind turbines of 60 m hub height each from different manufacturers, develops machine learning models to forecast very short‐term power production of the three wind turbine generators (WTG) and investigates the feasibility of embedded generation for a potential livestock industry in the area. Windographer software was used to characterize and simulate the net output power from these turbines using the wind speed of the potential site. Two hybrid models of adaptive neurofuzzy inference system (ANFIS) comprising genetic algorithm and particle swarm optimization (PSO) each for a turbine were developed to forecast very short‐term power output. The feasibility of embedded generation for typical medium‐scale agricultural industry was investigated using a weighted Weber facility location model. The analytical hierarchical process (AHP) was used for weight determination. From our findings, the WTG‐1 was selected based on its error performance metrics (root mean square error of 0.180, mean absolute SD of 0.091 and coefficient of determination of 0.914 and CT = 702.3 seconds) in the optimal model (PSO‐ANFIS). Criteria were ranked based on their order of significance to the agricultural industry as proximity to water supply, labour availability, power supply and road network. Also, as a proof of concept, the optimal location of the industrial facility relative to other criteria was X = 19.24 m, Y = 47.11 m . This study reveals the significance of resource forecasting and feasibility of embedded generation, thus improving the quality of preliminary resource assessment and facility location among site developers.     

Characterizing power performance and wake of a wind turbine under yaw and blade pitch

Wind turbine wakes have been recognized as a key issue causing underperformance in existing wind farms. In order to improve the performance and reduce the cost of energy from wind farms, one approach is to develop innovative methods to improve the net capacity factor by reducing wake losses. The output power and characteristics of the wake of a utility‐scale wind turbine under yawed flow is studied to explore the possibility of improving the overall performance of wind farms. Preliminary observations show that the power performance of a turbine does not degrade significantly under yaw conditions up to approximately 10°. Additionally, a yawed wind turbine may be able to deflect its wake in the near‐wake region, changing the wake trajectory downwind, with the progression of the far wake being dependent on several atmospheric factors such as wind streaks. Changes in the blade pitch angle also affect the characteristics of the turbine wake and are also examined in this paper. Copyright © 2015 John Wiley & Sons, Ltd.     

Empirical and numerical analysis of small wind turbine aerodynamic performance at a plateau terrain in Kenya

Kenya's energy depends on fossil fuels and the country is yet to embrace alternative sources that are environmentally friendly. In this paper, empirical and computational approaches are presented to investigate aerodynamic performance of Small Wind Turbine (SWT) operation at arid rural Mwingi-Kitui plateau region, Kenya. We used empirical statistics to represent wind resource, and Computational Fluid Dynamics (CFD) to address SWT aerodynamic performance at the site. The numerical simulations, employing Transition Shear Stress Transport (SST) model and fully mesh resolved rotor, were performed and results obtained compared with empirical methods. From the Wind Power Density (WPD) values, 44.50–85.48 W/m² between turbine hub heights 20 and 60 m, the site corresponds to wind class ≈1; hence unsuitable for grid-connected power generation. In addition, the numerical findings give useful insights to SWT aerodynamic performance with respect to empirical approach at a plateau terrain wind regime.     

Coherent Doppler lidar for wind farm characterization

Coherent Doppler lidar measurements are of increasing interest for the wind energy industry. Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three‐dimensional scanning Doppler lidar may provide a new basis for wind farm site selection, design and optimization. In this paper, the authors discuss Doppler lidar measurements obtained for a wind energy development. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically terrain effects, spatial variation of winds, power density and the effect of shear at different layers within the rotor swept area. Vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain‐following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. Doppler lidar data are used to estimate the spatial power density at hub height (for the period of the deployment). An example wind farm layout is presented for demonstration purposes based purely on lidar measurement, even though the lidar data acquisition period cannot be considered climatological. The strength of this approach is the ability to directly measure spatial variations of the wind field over the wind farm. Also, because Doppler lidar can measure winds at different vertical levels, an approach for estimating wind power density over the rotor swept area (rather than only the hub height) is explored. Finally, advanced vector retrieval algorithms have been applied to better characterize local wind variations and shear. Copyright © 2012 John Wiley & Sons, Ltd.     

Unsteady Aerodynamics of a Savonius wind rotor: a new computational approach for the simulation of energy performance

When compared with of other wind turbine the Savonius wind rotor offers lower performance in terms of power coefficient, on the other hand it offers a number of advantages as it is extremely simple to built, it is self-starting and it has no need to be oriented in the wind direction. Although it is well suited to be integrated in urban environment as mini or micro wind turbine it is inappropriate when high power is requested. For this reason several studies have been carried-out in recent years in order to improve its aerodynamic performance. The aim of this research is to gain an insight into the complex flow field developing around a Savonius wind rotor and to evaluate its performance. A mathematical model of the interaction between the flow field and the rotor blades was developed and validated by comparing its results with data obtained at Environmental Wind Tunnel (EWT) laboratory of the “Polytechnic University of Marche”.     

Technological evolution of onshore wind turbines—a market‐based analysis

Wind energy technology is evolving towards larger machines (longer blades, taller towers and more powerful generators). Scaling up wind turbines is a challenging task, which requires innovative solutions as well as new configurations and designs. The size of wind turbines (in terms of rotor diameter, hub height and rated power) has increased extraordinary from 30 m rotor diameter, 30 m of hub height and 300 kW rated power, usual in the late 1980s, to 92.7 m rotor diameter, 87.7 m of height and 2.1 MW on average at the end of 2014. However, technological evolution has not only been focused on the scaling up process but also on developing innovative solutions that minimize costs at the same time as they deal with aspects of different nature, such as grid code requirements, reliability, quality of the wind resource or prices and availability of certain commodities, among others. This paper analyses the evolution of wind technology from a market‐based perspective by identifying trends in the most relevant technological indicators at the same time as stressing the key differentiating aspects between regions/markets. Evolution and trends in indicators such as rated power, rotor diameter, hub height, specific power, wind class, drive train configuration and power control systems are presented and analysed, showing an intense and fast technological development, which is enabling wind energy to reduce costs and becoming increasingly more competitive with conventional fuel‐based generating technologies. © 2016 The Authors Wind Energy Published by John Wiley & Sons Ltd.