Climate change implications for wind power resources in the Northwest United States

Using statistically downscaled output from four general circulation models (GCMs), we have investigated scenarios of climate change impacts on wind power generation potential in a five-state region within the Northwest United States (Idaho, Montana, Oregon, Washington, and Wyoming). All GCM simulations were extracted from the standardized set of runs created for the Intergovernmental Panel on Climate Change (IPCC). Analysis of model runs for the 20th century (20c3m) simulations revealed that the direct output of wind statistics from these models is of relatively poor quality compared with observations at airport weather stations within each state. When the GCM output was statistically downscaled, the resulting estimates of current climate wind statistics are substantially better. Furthermore, in looking at the GCM wind statistics for two IPCC future climate scenarios from the Special Report on Emissions Scenarios (SRES A1B and A2), there was significant disagreement in the direct model output from the four GCMs. When statistical downscaling was applied to the future climate simulations, a more coherent story unfolded related to the likely impact of climate change on the region's wind power resource. Specifically, the results suggest that summertime wind speeds in the Northwest may decrease by 5–10%, while wintertime wind speeds may decrease by relatively little, or possibly increase slightly. When these wind statistics are projected to typical turbine hub heights and nominal wind turbine power curves are applied, the impact of the climate change scenarios on wind power may be as high as a 40% reduction in summertime generation potential.     

基于RBF神经网络的桨距角控制策略

针对风力发电系统数学模型复杂,受参数变化和外部干扰严重,具有非线性、时变、强耦合的特点,将神经网络控制引入到风力发电控制系统中,将神经网络控制器作为变桨距系统的控制器,在风速高于额定风速的情况下,根据风速的变化调整桨叶桨距角,从而调节发电机的输出功率,使风力发电机组的输出功率保持稳定.最后,利用Simulink搭建整个...     

低空急流条件下水平轴风力机风轮气动特性的研究

为阐明低空急流条件下风力机风轮的气动特性,基于工程化的边界层风速模型和Von Karman谱模型建立不同来流的脉动风场,对比研究低空急流条件下NREL 5 MW风力机风轮的输出功率和气动载荷的变化规律。结果表明:如果仅以轮毂高度处的风速作为风力机变桨控制的依据,与均匀来流和剪切来流相比较,低空急流条件下,虽然来流风功率明显增大,但风轮的输出功率在较高风速时反而减小;风轮所受的不平衡气动载荷,包括横向力、纵向力、偏航力矩和倾覆力矩在较高风速时小于剪切来流的结果;且仅以轮毂高度处的风速预测得到的风轮输出功率高于实际结果,其最大相对误差为89.4%。因此,低空急流条件下,为提高风能利用率和风轮输出功率的预测精度,应考虑不同高度位置处的风速大小对风力机进行变桨控制和功率预测。     

The influence of non‐logarithmic wind speed profiles on potential power output at Danish offshore sites

Detailed knowledge of mean wind speed profiles is essential for properly assessing the power output of a potential wind farm. Since atmospheric stratification plays a crucial role in affecting wind speed profiles, obtaining a detailed picture of the climatology of stability conditions at a given site is very important. In the present study, long time series from offshore measurement sites around Denmark are analysed, with the aim of quantifying the role of atmospheric stability in wind speed profiles and in our ability to model them. A simple method for evaluating stability is applied, and the resulting statistics of the atmospheric stratification is thoroughly studied. A significant improvement in the mean wind speed profile prediction is obtained by applying a stability correction to the logarithmic profiles suitable for neutral conditions. These results are finally used to estimate power densities at different heights. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by the Weather Research and Forecasting model using seven sets of simulations with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights ranging from 10 to 160 m, wind shears, temperatures and surface turbulent fluxes from seven sets of hindcasts are evaluated against observations at Høvsøre, Denmark. The ability of these hindcast sets to simulate mean wind speeds, wind shear, and their time variability strongly depends on atmospheric static stability. Wind speed hindcasts using the Yonsei University PBL scheme compared best with observations during unstable atmospheric conditions, whereas the Asymmetric Convective Model version 2 PBL scheme did so during near‐stable and neutral conditions, and the Mellor–Yamada–Janjic PBL scheme prevailed during stable and very stable conditions. The evaluation of the simulated wind speed errors and how these vary with height clearly indicates that for wind power forecasting and wind resource assessment, validation against 10 m wind speeds alone is not sufficient. Copyright © 2012 John Wiley & Sons, Ltd.     

Power limitations and energy yield evaluation for wind farms operating in island systems

Wind farms operating in island systems are subject to output power limitations, related with technical constraints of the conventional generating units, namely the minimum loading levels of the thermal units (technical minima) and a dynamic penetration limit, applied for stability purposes. Evaluation of the expected wind energy yield in isolated island systems requires, therefore, proper consideration, not only of the prevailing wind conditions at the installation site, but also of the power limitations imposed by the system, which ultimately depend on the total load demand. In the paper, a methodology is presented for the evaluation of the wind energy absorption capability of island systems and the expected energy yield of wind farms operating therein. This methodology is currently applied in Greece for the determination of the power restrictions applied to existing and new wind farms, to schedule new wind capacity tenders and for the evaluation of the expected energy yield of new investments for permitting and financing purposes.     

Application of artificial neural networks for the wind speed prediction of target station using reference stations data

In this study, artificial neural networks (ANNs) were applied to predict the mean monthly wind speed of any target station using the mean monthly wind speeds of neighboring stations which are indicated as reference stations. Hourly wind speed data, collected by the Turkish State Meteorological Service (TSMS) at 8 measuring stations located in the eastern Mediterranean region of Turkey were used. The long-term wind data, containing hourly wind speeds, directions and related information, cover the period between 1992 and 2001. These data were divided into two sections. According to the correlation coefficients, reference and target stations were defined. The mean monthly wind speeds of reference stations were used and also corresponding months were specified in the input layer of the network. On the other hand, the mean monthly wind speed of the target station was utilized in the output layer of the network. Resilient propagation (RP) learning algorithm was applied in the present simulation. The hidden layers and output layer of the network consist of logistic sigmoid transfer function (logsig) and linear transfer function (purelin) as an activation function. Finally, the values determined by ANN model were compared with the actual data. The maximum mean absolute percentage error was found to be 14.13% for Antakya meteorological station and the best result was found to be 4.49% for Mersin meteorological station.     

Sizing and control of trailing edge flaps on a smart rotor for maximum power generation in low fatigue wind regimes

An extension of the spectrum of applicability of rotors with active aerodynamic devices is presented in this paper. Besides the classical purpose of load alleviation, a secondary objective is established: optimization of power capture. As a first step, wind speed regions that contribute little to fatigue damage have been identified. In these regions, the turbine energy output can be increased by deflecting the trailing edge (TE) flap in order to track the maximum power coefficient as a function of local, instantaneous speed ratios. For this purpose, the TE flap configuration for maximum power generation has been using blade element momentum theory. As a first step, the operation in non‐uniform wind field conditions was analysed. Firstly, the deterministic fluctuation in local tip speed ratio due to wind shear was evaluated. The second effect is associated with time delays in adapting the rotor speed to inflow fluctuations caused by atmospheric turbulence. The increase in power generation obtained by accounting for wind shear has been demonstrated with an increase in energy production of 1%. Finally, a control logic based on inflow wind speeds has been devised, and the potential of enhanced power generation has been shown by time‐domain simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

Characterizing future large,rapid changes in aggregated wind power using Numerical Weather Prediction spatial fields

A critical limiting factor to the successful deployment of a large proportion of wind power in power systems is its predictability. Power system operators play a vital role in maintaining system security, and this task is greatly aided by useful characterizations of future system operations. A wind farm power forecast generally relies on the forecast output from a Numerical Weather Prediction (NWP) model, typically at a single grid point in the model to represent the wind farm's physical location. A key limitation of this approach is the spatial misplacement of weather features often found in NWP forecasts. This paper presents a methodology to display wind forecast information from multiple grid points at hub height around the wind farm location. If the raw forecast wind speeds at hub height at multiple grid points were to be displayed directly, they would be misleading as the NWP outputs take account of the estimated local surface roughness and terrain at each grid point. Hence, the methodology includes a transformation of the wind speed at each grid point to an equivalent value that represents the surface roughness and terrain at the chosen single grid point for the wind farm site. The chosen‐grid‐point‐equivalent wind speeds for the wind farm can then be transformed to available wind farm power. The result is a visually‐based decision support tool which can help the forecast user to assess the possibilities of large, rapid changes in available wind power from wind farms. A number of methods for displaying the field for multiple wind farms are discussed. The chosen‐grid‐point‐equivalent transformation also has other potential applications in wind power forecasting such as assessing deterministic forecast uncertainty and improving downscaling results. Copyright © 2008 John Wiley & Sons, Ltd.     

A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site

This paper proposes the use of a new Measure-Correlate-Predict (MCP) method to estimate the long-term wind speed characteristics at a potential wind energy conversion site. The proposed method uses the probability density function of the wind speed at a candidate site conditioned to the wind speed at a reference site. Contingency-type bivariate distributions with specified marginal distributions are used for this purpose. The proposed model was applied in this paper to wind speeds recorded at six weather stations located in the Canary Islands (Spain). The conclusion reached is that the method presented in this paper, in the majority of cases, provides better results than those obtained with other MCP methods used for purposes of comparison. The metrics employed in the analysis were the coefficient of determination (R²) and the root relative squared error (RRSE). The characteristics that were analysed were the capacity of the model to estimate the long-term wind speed probability distribution function, the long-term wind power density probability distribution function and the long-term wind turbine power output probability distribution function at the candidate site.     

PSCAD/EMTDC-Based Modeling and Analysis of a Gearless Variable Speed Wind Turbine

This paper presents dynamic modeling and simulation of a grid connected variable speed wind turbine (VSWT) using PSCAD/EMTDC, a widely used power system transient analysis tool. The variable speed wind system with a direct-drive generator and power electronics interface is modeled for dynamic analysis. Component models and equations are addressed and their implementations into PSCAD/EMTDC are described. Controllable power inverter strategy is intended for capturing the maximum energy from varying wind speed and maintaining reactive power generation at a pre-determined level for constant power factor or voltage regulation. The component models and entire control scheme are constructed by user-defined function provided in the program. Simulation studies provide control performance and dynamic behavior of a gearless VSWT under varying wind speeds. In addition, the system responses to network fault conditions have been simulated. This modeling study can be employed to evaluate the control scheme, output performance and impacts of a VSWT on power grid at planning or designing stage.     

Evaluation of wind farm efficiency and wind turbine wakes at the Nysted offshore wind farm

Here, we quantify relationships between wind farm efficiency and wind speed, direction, turbulence and atmospheric stability using power output from the large offshore wind farm at Nysted in Denmark. Wake losses are, as expected, most strongly related to wind speed variations through the turbine thrust coefficient; with direction, atmospheric stability and turbulence as important second order effects. While the wind farm efficiency is highly dependent on the distribution of wind speeds and wind direction, it is shown that the impact of turbine spacing on wake losses and turbine efficiency can be quantified, albeit with relatively large uncertainty due to stochastic effects in the data. There is evidence of the ‘deep array effect’ in that wake losses in the centre of the wind farm are under‐estimated by the wind farm model WAsP, although overall efficiency of the wind farm is well predicted due to compensating edge effects. Copyright © 2010 John Wiley & Sons, Ltd.     

WEPAS和WAsP在复杂地形条件下的适应性

利用WEPAS和WAsP软件分别计算了南澳风电场的发电量,在充分考虑岛屿型复杂地形地貌条件下对2个软件的计算结果进行对比分析,研究表明,对于地形复杂的南澳风电场,WEPAS和WAsP软件发电量计算结果与实际发电量差值分别为-15.18%和28.02%。其中,WEPAS软件计算的风电场风速和风功率密度上下限偏差较小,结果比较平滑;WAsP软件计算结果比实际值偏高,但是单台风机平均风速和发电量计算结果与实际风况变化趋势比较一致。对上述结论的可能原因进行分析,初步显示2种软件的风场风况计算模式在复杂地形条件下存在较大的不足,风场诊断模式不能较好地模拟复杂地形条件下大气边界层风廓线的实际流动状况。因此,需要改进模式,研发出适用于大气边界层流动计算的风廓线模型、湍流模型和地表函数模型。     

Wind-powered electric water-pumping system installed in a remote location

In December 1996, the country's first wind-powered, electric water-pumping system was successfully installed at the Ministry of Water Resources (MWR) Heelat Ar Rakah Camp, a remote location some 900 kilometres south of Muscat, the capital city of Oman. A weather-monitoring station comprising temperature, wind speed/direction, humidity and barometric pressure equipment was also installed to investigate the relationship between weather conditions and power output. Both systems are still in operation and are providing valuable data for analysis. This paper investigates the pump's output at different wind speeds and monthly water output against average wind velocity and compares the results with the design output values provided by the system manufacturer. Problems encountered in meeting the irrigation requirements at the camp during periods of low wind are discussed and solutions proposed. The potential of utilizing surplus energy generated during periods of high wind is under investigation. The paper concludes by assessing and analysing the role of wind power amongst other renewable energy sources, in the abstraction and desalination of groundwater supplies.     

Rotational speed adjustment of axial flow fans to maximize net power output for direct dry cooling power generating units

The power consumption of axial flow fans may account for more than 1% of the rated power output of the power generating unit, so it is of benefit to the energy efficiency of the power generating unit to propose an operation adjustment approach to axial flow fans. On the basis of representative 2 × 600 MW direct dry cooling generating units, a computational model of air‐side flow and heat transfer of an air‐cooled condenser (ACC) combined with exhaust steam condensation is developed, by which the airflow rate, inlet air temperature of ACCs, the power consumption of axial flow fans, turbine backpressure, and net power output of power generating units at various wind speeds and in various wind directions are obtained. The results show that the net power output in the presence of winds always decreases when the rational speeds of the first upwind row axial flow fans increase from the rated speed of 79 rpm by 10% to 86.9 rpm. However, the net power output will increase in various wind directions if the rational speeds of all the fans except the upwind first row fans increase to 86.9 rpm. This can contribute to the optimal operation of the ACC by rotational speed adjustment of axial flow fans.     

Output power dispatch control for a wind farm in a small power system

Nowadays, a wind turbine generator (WTG) is required to provide control capabilities as the output power of WTG fluctuates. Under this scenario, this paper proposes an output power control method of a wind farm (WF) connected to a small power system using pitch angle control. In this control approach, the WF output power control is achieved by two control levels: central and local. In the central control, the WF output power command is determined by considering the frequency deviations and wind speeds using a fuzzy function. Then, the local output power commands for each of the WTGs are based on the proposed dispatch control. In the proposed dispatch control, the output commands of each WTG are determined by considering wind conditions for each of the WTGs. The simulation results by using an actual detailed model for the wind power system show the effectiveness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd.     

A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.     

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.     

Analysis of wind power generation and prediction using ANN: A case study

Many developing nations, such as India have embarked upon wind energy programs for areas experiencing high average wind speeds throughout the year. One of the states in India that is actively pursuing wind power generation programs is Tamil Nadu. Within this state, Muppandal area is one of the identified regions where wind farm concentration is high. Wind energy engineers are interested in studies that aim at assessing the output of wind farms, for which, artificial intelligence techniques can be usefully adapted. The present paper attempts to apply this concept for assessment of the wind energy output of wind farms in Muppandal, Tamil Nadu (India). Field data are collected from seven wind farms at this site over a period of 3 years from April 2002 to March 2005 and used for the analysis and prediction of power generation from wind farms. The model has been developed with the help of neural network methodology. It involves three input variables—wind speed, relative humidity and generation hours and one output variable-energy output of wind farms. The modeling is done using MATLAB toolbox. The model accuracy is evaluated by comparing the simulated results with the actual measured values at the wind farms and is found to be in good agreement.