Geographic aggregation of wind power—an optimization methodology for avoiding low outputs

This work investigates macro‐geographic allocation as a means to improve the performance of aggregated wind power output. The focus is on the spatial smoothing effect so as to avoid periods of low output. The work applies multi‐objective optimization, in which two measures of aggregated wind power output variation are minimized, whereas the average output is maximized. The results show that it is possible to allocate wind power so that the frequency of low outputs is substantially reduced, while maintaining the average output at around 30% of nameplate capacity, as compared with the corresponding output of 20% for the present allocation system. We conclude that in a future, fully electrically integrated Europe, geographic allocation can substantially reduce instances of low aggregate output, while impairing little on capacity factor and at the same time providing reduction in of short‐term jumps in output. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of potential power production at on‐ and offshore sites

This article presents analyses of the potential power production from turbines located in the near‐shore and offshore environment relative to an onshore location, using half‐hourly average wind speed data from four sites in the Danish wind monitoring network. These measurement sites are located in a relatively high wind speed environment, and data from these sites indicate a high degree of spatial coherence. For these sites and representative turbine specifications (rated power 1·3–2 W) the fraction of time with power output in excess of 500 kW is twice as high for the offshore location as for the land site. Also, the fraction of time with negligible power production (defined as <100 kW output from the turbines described herein) is less than 20% for the offshore site and twice as high at the land‐based location. Capacity factors are higher for coastal sites than for the land site, and the annual capacity factor for the offshore location is twice that of the land site. Potential power output at the offshore site exhibits approximately the same seasonal variation as at the land site but little diurnal variation. Copyright © 2001 John Wiley & Sons, Ltd.     

The energy storage system output control strategy to improve theshort term windpower forecastingaccuracy rate

目前对于储能系统应用于平抑新能源发电的波动性、移峰填谷等场景的控制策略已有文献研究,但对于风功率预测准确率影响风电场效益的机制下储能系统应用的可行性尚未见研究。本文提出了一种以减小风电场短期功率预测偏差为目标的储能系统出力控制策略,控制策略以风电场实时出力数据（秒级）为数据源,采用线性外推加以移动平均优化的方法预测下一时刻风电场出力,通过比较风电场短期功率预测值与实时预测值,计算储能系统期望出力,并根据储能系统不同SOC区间内的出力能力进行约束,输出储能系统出力指令,最后进行了仿真验证。结果表明,本文提出的储能系统出力控制策略,能够使风电场通过配置储能系统,减少短期功率预测准确度考核,对风电场的精益化运行具有指导意义。     

Horizontal axis wind turbine systems: optimization using genetic algorithms

A method for the optimization of a grid‐connected wind turbine system is presented. The behaviour of the system components is coupled in a non‐linear way, and optimization must take into account technical and economical aspects of the complete system design. The annual electrical energy cost is estimated using a cost model for the wind turbine rotor, nacelle and tower and an energy output model based on the performance envelopes of the power coefficient of the rotor, C_P, on the Weibull parameters k and c and on the power law coefficient α of the wind profile. In this study the site is defined with these three parameters and the extreme wind speed V_max. The model parameters vary within a range of possible values. Other elements of the project (foundation, grid connection, financing cost, etc.) are taken into account through coefficients. The optimal values of the parameters are determined using genetic algorithms, which appear to be efficient for such a problem. These optimal values were found to be very different for a Mediterranean site and a northern European site using our numerical model. Optimal wind turbines at the Mediterranean sites considered in this article have an excellent profitability compared with reference northern European wind turbines. Most of the existing wind turbines appear to be well designed for northern European sites but not for Mediterranean sites. Copyright © 2001 John Wiley & Sons, Ltd.     

Wind turbine generator trends for site‐specific tailoring

Turbine optimization for specific wind regimes and climate conditions is becoming more common as the market expands into new territories (offshore, low‐wind regimes) and as technology matures. Tailoring turbines for specific sites by varying rotor diameter, tower height and power electronics may be a viable technique to make wind energy more economic and less intermittent. By better understanding the wind resource trends and evaluating important wind turbine performance parameters such as specific power (ratio of rated power and rotor swept area), developers and operators can optimize plant output and better anticipate operational impacts. This article presents a methodology to evaluate site‐specific wind data for turbine tailoring. Wind characteristics for the Tehachapi wind resource area in California were utilized for this study. These data were used to evaluate the performance of a range of wind turbine configurations. The goal was to analyse the variations in wind power output for the area, assess the changes in these levels with the time of day and season and determine how turbine configuration affects the output. Wind turbine output was compared with California statewide system electrical demand to evaluate the correlation of the wind resource site with local peak demand loads. A comparison of the commercial value of electricity and corresponding wind generation is also presented using a time‐dependent valuation methodology. Copyright © 2005 John Wiley & Sons, Ltd.     

考虑风电不确定性的电热系统经济调度

随着风电等新能源大规模并网,其出力的不确定性给电力系统日前调度带来很大挑战。传统的研究方法多是假设风电功率预测误差服从某种概率分布,但风电功率预测误差受到多种因素影响,概率分布模型无法准确描述其特性。为此,采用基于神经网络的组合预测方法对风电功率误差进行建模,再将预测的风电误差加入到包含热电机组、火电机组、风电、储热装置和电锅炉的热电联合优化调度模型中,最后以实际的10机系统为例进行仿真,分析了风电预测误差对机组出力、风电消纳及调度成本的影响。结果表明,与传统方法相比,所建模型可减少机组燃煤成本与旋转备用成本,降低了经济调度成本,提高了风电消纳水平。     

Experimental verification of computational predictions in power generation variation with layout of offshore wind farms

The optimization of wind farms with respect to spatial layout is addressed experimentally. Wake effects within wind turbine farms are well known to be deleterious in terms of power generation and structural loading, which is corroborated in this study. Computational models are the predominant tools in the prediction of turbine‐induced flow fields. However, for wind farms comprising hundreds of turbines, reliability of the obtained numerical data becomes a growing concern with potentially costly consequences. This study pursues a systematic complementary theoretical, experimental and numerical study of variations in generated power with turbine layout of an 80 turbine large wind farm. Wake effects within offshore wind turbine arrays are emulated using porous discs mounted on a flat plate in a wind tunnel. The adopted approach to reproduce experimentally individual turbine wake characteristics is presented, and drag measurements are argued to correctly capture the variation in power generation with turbine layout. Experimental data are juxtaposed with power predictions using ANSYS WindModeller simulation suite. Although comparison with available wind farm power output data has been limited, it is demonstrated nonetheless that this approach has potential for the validation of numerical models of power loss due to wake effects or even to make a direct physical prediction. The approach has even indicated useful data for the improvement of the physics within numerical models. Copyright © 2014 John Wiley & Sons, Ltd.     

Time series modelling of power output for large‐scale wind fleets

Simulations of power systems with high wind penetration need to represent the stochastic output of the wind farms. Many studies use historic wind data directly in the simulation. However, even if historic data are used to drive the realized wind output in scheduling simulations, a model of the wind's statistical properties may be needed to inform the commitment decisions for the dispatchable units. There are very few published studies that fit models to the power output of nation‐sized wind fleets rather than the output at a single location. We fitted a time series model to hourly, time‐averaged, aggregated wind power data from New Zealand, Denmark and Germany, based on univariate, second‐order autoregressive drivers. Our model is designed to reproduce the asymptotic distribution of power output, the diurnal variation and the volatility of power output over timescales up to several hours. For the cases examined here, it was also found to provide a generally good representation of the overall distribution of power output changes and the variation of volatility with power output level, as well as an acceptable representation of the distribution of calm periods. Copyright © 2011 John Wiley & Sons, Ltd.     

Model of a synthetic wind speed time series generator

Wind energy has assumed a great relevance in the operation and planning of today's power systems due to the exponential increase of installations in the last 10 years. For this reason, many performed studies have looked at suitable representations of wind generation for power system analysis. One of the main elements to consider for this purpose is the model of the wind speed that is usually required as input. Wind speed measurements may represent a solution for this problem, but, for techniques such as sequential Monte Carlo simulation, they have to be long enough in order to describe a wide range of possible wind conditions. If these information are not available, synthetic wind speed time series may be a useful tool as well, but their generator must preserve statistical and stochastic features of the phenomenon. This paper deals with this issue: a generator for synthetic wind speed time series is described and some statistical issues (seasonal characteristics, autocorrelation functions, average values and distribution functions) are used for verification. The output of the model has been designed as input for sequential Monte Carlo simulation; however, it is expected that it can be used for other similar studies on wind generation. Copyright © 2007 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.     

基于偏航尾流模型的风电场功率协同优化研究

为减小风电场尾流效应的影响,提升风电场整体发电量,提出一种基于偏航尾流模型的风电场功率协同优化方法。首先建立风电场偏航尾流模型,该模型包括用于计算单机组尾流速度分布的Jensen-Gaussian尾流模型、尾流偏转模型及多机组尾流叠加模型,对各机组风轮前来流风速进行求解;再根据来流风速计算风电场输出功率,并以风电场整体输出功率最大为优化目标,利用拟牛顿算法协同优化各机组轴向诱导因子和偏航角度。以4行4列方形布置的16台NREL-5 MW风电机组为对象进行仿真研究。结果表明,所提出的基于偏航尾流模型的风电场功率协同优化方法能显著提升风电场整体输出功率。     

基于电池储能系统和双重扩展卡尔曼滤波的风能发电智能调度技术研究

风能等新能源发电系统在供电体系中的占比越来越大,但其随机性和波动性问题,将风力发电厂输出的电力直接向电网调度会造成安全隐患。为了解决这一问题,基于电池储能系统提出了一种风能发电智能调度技术,该技术以风力发电动力学模型和电池储能系统状态模型为基础,利用双重扩展卡尔曼滤波算法实现了风能发电系统的稳定输出。以某地风速实测数据和电网需求功率为参考,对不同算法的输出功率预测值进行了仿真分析和实验对比。结果表明：提出的改进算法预测的风速值误差相比于传感器观测值平均误差降低了28%以上,可以更准确地提供发电系统输出功率;提出的智能调度技术可以使电压波动幅度降低60%以上,系统整体输出功率稳定在参考功率附近,误差不超过2%,有一定的实用意义。     

Economic feasibility of electricity generation from wind farms: A case study

Environmental problems, population growth, and the recent energy crisis have emphasized the need for zero-emission technologies while also ensuring economic feasibility. This work presents the economic advantages of using wind energy for power generation in Iran. A theoretical model is developed, which predicts the output power under various geographical and operating conditions. The wind data (speed and direction) of 2-h interval long-term period from December 2010 to October 2015 was adopted and analyzed to evaluate the levelized costs of electricity (COE) for power generation from wind farms (Arsanjan, Lamerd, and Abadeh) for the year 2018 per time. The influence of two important geographical factors namely winds speed and air humidity on output power also was studied. The results showed that the output power increases continuously when the wind speed varies from 2.0 to 2.6 m/s probably due to the compression of air passing through the wind turbine.     

Potentials of wind energy development for water pumping in Jordan

The potential of the development of water pumping using wind energy in Jordan was studied. Underground water can be pumped using wind power. Based on available wind data eleven wind sites were considered. The results show that these sites can be divided, in terms of the annual amount of pumped water, into three categories. One is considered “favorable”, which includes Ras Muneef, Mafraq, and Aqaba. Their water output adds up to most of water produced from all eleven sites combined (about 64%). Others are considered to be “promising”, which include H-5, Irbid, and Ma'an. Their water output adds up to about to 28% of all water pumped at all sites combined. The rest of sites considered are found to be “poor”, which include H-4, Amman, Queen Alia's Airport, Shoubak, and Deiralla, with much smaller amounts of water output. Their combined water output adds up to less than 8% of all site combined.     

A review on development of offshore wind energy conversion system

Wind energy conversion system, aiming to convert mechanical energy of air flow into electrical energy has been widely concerned in recent decades. According to the installation sites, the wind energy conversion system can be divided into land-based wind conversion system and offshore wind energy conversion (OWEC) system. Compared to land-based wind energy technology, although OWEC started later, it has attracted more attentions due to its significant advantages in sufficient wind energy, low wind shear, high power output and low land occupancy rate. In this paper, the principle of wind energy conversion and the development status of offshore wind power in the world are briefly introduced at first. And then, the advantages and disadvantages of several offshore wind energy device (OWED), such as horizontal axis OWED, vertical axis OWED and cross axis OWED are compared. Subsequently, several major constraints, such as complex marine environment, deep-sea power transmission and expensive cost of equipment installation faced by offshore wind conversion technology are presented and comprehensively analysed. Finally, based on the summary and analysis of some emerging technologies and the current situation of offshore wind energy utilization, the development trend of offshore wind power is envisioned. In the future, it is expected to witness multi-energy complementary, key component optimization and intelligent control strategy for smooth energy generation of offshore wind power systems.     

风电场中抽水蓄能电站的优化配置

为解决电力系统接入风电容量超过一定比例后引起的调峰及弃风问题,改善风电场功率输出特性,可采用与风电场配套建设抽水蓄能电站的模式。在建立风电场及抽水蓄能电站运行模型的基础上,以风电—抽水蓄能电站经济效益为目标,采用一种新的自适应遗传算法对风电—抽水蓄能电站的最佳容量配比进行求解。通过对一实际算例的仿真,表明配置适当容量的抽水蓄能电站可提高风电场的综合效益。     

Simulation of wind energy output at Guajira, Colombia

A methodology is developed to estimate the chord distribution airfoil and blade twist along the radius of the blade by using axial and angular moment conservation equations, blade element theory and optimization processes. This methodology takes into account the concept related with getting wind power for different chord blade values and selecting one that facilitates to get the maximum value for wind power. Simulation of power generation output was carried out by using a wind-speed probability distribution function (PDF) obtained from data collected at the Guajira region of Colombia.     

风电场风功率实时预测效果综合评价方法

超短期风电功率预测对含大规模风电的电力系统安全经济运行有着重要意义。但目前对预测结果的评价均停留在常规统计学指标上,缺乏合理的评价体系来评价某特定风电场所选取预测模型的优劣。简述了目前风电功率预测结果评价指标的不足,提出一种基于预测误差评价和预报考核等指标的风电场输出功率实时预测效果评估方法,为不同地区风电场根据其风电输出功率变化的特点,选择预测模型以及风电场输出功率预测效果的工程检验提供依据。最后,利用吉林省某风电场实测数据,采用该评估方法对不同预测模型的实时预测结果进行分析评价,实现了该风电场不同预测模型间的择优,验证了该评价方法的指导价值。     

风/光混合发电系统的优化方法综述

为了从混合发电系统中获得足够经济可靠的电力,其优化方法的选择非常关键,分析了风/光混合发电系统的结构,系统梳理了国外风/光混合发电系统的软件优化法、传统优化方法、人工智能法等优化方法,并对混合发电系统的各种优化方法进行了总结及展望,可为国内风/光混合发电系统优化问题的合理解决提供参考。