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Certain applications, such as analysing the effect of a wind farm on grid frequency regulation, require several years of wind power data measured at intervals of a few seconds. We have developed a method to generate days to years of non‐stationary wind speed time series sampled at high rates by combining measured and simulated data. Measured wind speed data, typically 10–15 min averages, capture the non‐stationary characteristics of wind speed variation: diurnal variations, the passing of weather fronts, and seasonal variations. Simulated wind speed data, generated from spectral models, add realistic turbulence between the empirical data. The wind speed time series generated with this method agree very well with measured time series, both qualitatively and quantitatively. The power output of a wind turbine simulated with wind data generated by this method demonstrates energy production, ramp rates and reserve requirements that closely match the power output of a turbine simulated turbine with measured wind data. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Matti Koivisto Kaushik Das Feng Guo Poul Srensen Edgar Nuo Nicolaos Cutululis Petr Maule 《Wiley Interdisciplinary Reviews: Energy and Environment》2019,8(3)
The increasing share of variable renewable energy (VRE) generation poses challenges to power systems. Possible challenges include adequacy of reserves, planning and operation of power systems, and interconnection expansion studies in future power systems with very different generation patterns compared to today. To meet these challenges, there is a need to develop models and tools to analyze the variability and uncertainty in VRE generation. To address the varied needs, the tools should be versatile and applicable to different geographical and temporal scales. Time series simulation tools can be used to model both today and future scenarios with varying VRE installations. Correlations in Renewable Energy Sources (CorRES) is a simulation tool developed at Technical University of Denmark, Department of Wind Energy capable of simulating both wind and solar generation. It uses a unique combination of meteorological time series and stochastic simulations to provide consistent VRE generation and forecast error time series with temporal resolution in the minute scale. Such simulated VRE time series can be used in addressing the challenges posed by the increasing share of VRE generation. These capabilities will be demonstrated through three case studies: one about the use of large‐scale VRE generation simulations in energy system analysis, and two about the use of the simulations in power system operation, planning, and analysis. This article is categorized under:
- Wind Power > Systems and Infrastructure
- Energy Infrastructure > Systems and Infrastructure
- Energy Systems Economics > Systems and Infrastructure
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The main goal of this paper is to establish the present state of the art for wind farm control. The control area that will be focused on is the mechanical/aerodynamic part, which includes the wind turbines, their power production, fatigue and wakes affecting neighbouring wind turbines. The sub‐objectives in this area of research are as follows: (i) maximizing the total wind farm power production; (ii) following a reference for the total wind farm active power; and (iii) doing this in a manner that minimizes fatigue loading for the wind turbines in the farm. Each of these sub‐objectives is discussed, including the following important control issues: choice of input and output, control method and modelling used for controller design and simulation. The available literature from industry is also considered. Finally, a conclusion is presented discussing the established results, open challenges and necessary research. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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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. 相似文献
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提出一种利用时间序列分析方法建立的回归模型,根据该模型可以在线进行递推预测电力系统周波变化趋势 相似文献
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针对当前风力发电系统输出功率随机波动的问题,以永磁同步风力发电机(PMSG)与直流侧储能系统(钒氧化还原电池)整合的风力发电系统为基础,进行数字仿真建模,采用MATLAB/Simulink软件对固定负载,变化风速工况;固定风速,负荷瞬变工况;风速和负荷同时变化工况;进行了仿真试验和分析.结果表明,对于采用储能技术的风电场并网功率随机波动的平抑控制,可以利用蓄电池的充放电特性,在风速变化以及负荷瞬变时进行功率平衡的调节. 相似文献
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In this paper, critical review of various work done in the areas of wind energy resource, modelling of wind energy conversion system (WECS) and issues regarding wind power integration into the grid are presented with the aim of examining the development, progress, achievements and direction of research. Some of the findings show that every site is unique; therefore, no generic conclusion can be drawn with regards to wind characteristics and the wind power potential of locations. The study also reveals that there is no single model of WECS. The model to be adopted will depend on the problem to be solved. This paper is useful in providing background details for wind turbine designers, researchers and practical engineers who are new in the field of wind energy. 相似文献
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As the share of variable generation in power systems increases, there is increasing value in more flexible use and generation of electricity. The paper compares the economic value of several flexibility options in a large power system with a large amount of reservoir hydro power. Generation planning models are needed to consider the impact of flexibility options on other investments in a power system. However, generation planning models do not include all the relevant operational details. The approach in the paper combines a generation planning model with a unit commitment and dispatch model. The results demonstrate the value of coupling the heat and power sectors and the value of transmission. Low-cost electricity storage does not appear to be as decisive in the Northern European context with wind power as the main variable generation source. The paper also addresses methodological issues related to the inclusion of operational constraints in generation planning. 相似文献
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The availability of day‐ahead production forecast is an important step toward better dispatchability of wind power production. However, the stochastic nature of forecast errors prevents a wind farm operator from holding a firm production commitment. In order to mitigate the deviation from the commitment, an energy storage system connected to the wind farm is considered. One statistical characteristic of day‐ahead forecast errors has a major impact on storage performance: errors are significantly correlated along several hours. We thus use a data‐fitted autoregressive model that captures this correlation to quantify the impact of correlation on storage sizing. With a Monte Carlo approach, we study the behavior and the performance of an energy storage system using the autoregressive model as an input. The ability of the storage system to meet a production commitment is statistically assessed for a range of capacities, using a mean absolute deviation criterion. By parametrically varying the correlation level, we show that disregarding correlation can lead to an underestimation of a storage capacity by an order of magnitude. Finally, we compare the results obtained from the model and from field data to validate the model. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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The current development of wind power in China was presented in this paper. Many regions such as Xinjiang Uygur Autonomous
Region, Inner Mongolia Autonomous Region and southeast coastal region, etc. in China have abundant wind energy resource. At
the same time, the utilization of wind power in China has been developing quickly and its prospect is promising in spite of
many some obstacles. With the implementation of the Renewable Energy Law, some previous obstacles have been or are being eliminated.
Much investment and many enterprises start to enter this field. In spite of this, there still exist some financial and technological
obstacles. One of the technological obstacles is the stability of local power grid owing to the increasing proportion of the
wind power capacity. Because the centralized development mode of wind power was adopted, the quick fluctuation of wind speed
will influence the voltage and frequency stability of local power grid. In addition, large wind farm has little dispatching
ability because of the uncontrollability, randomness and fluctuation of natural incoming wind. To erase these obstacles, a
novel hybrid power system combining wind farm and small gas turbine power plants is discussed. 相似文献
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目前风功率预测多为风功率期望的点预测,且以采样间隔较大的功率序列作为建模序列,这样会降低预测模型对风功率时序特征模拟的准确度和可信度。文中基于小采样间隔风功率序列,提出ARMAX-GARCH风功率预测模型。通过构造风功率新息序列,结合小时平均风功率序列,建立ARMAX点预测模型,采用BIC最小信息准则和相关性分析实现模型定阶和外生变量选择;采用GARCH模型模拟残差的波动特性实现区间预测。以海岛微电网实测风功率数据为例,进行提前1 h风功率预测。结果表明,与持续法、ARMA和RBF神经网络相比,该预测模型能显著提高风功率期望的点预测精度并具有较好的区间预测效果。 相似文献
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基于ARMA模型的风电场风速短期预测 总被引:4,自引:1,他引:3
通过分析达坂城风电场风速数据并建立ARMA模型,基于时间序列分析法实现了提前1h风速预测,分析预测结果证明预测时间和风速震荡性是影响风速预测精度的主要因素,为更长时间的风速预测提供理论基础。 相似文献
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Predictions of wind energy potential in a given region are based on on‐location observations. The time series of these observations would later be analysed and modelled either by a probability density function (pdf) such as a Weibull curve to represent the data or recently by soft computing techniques, such as neural networks (NNs). In this paper, discrete Hilbert transform has been applied to characterize the wind sample data measured on ?zmir Institute of Technology campus area which is located in Urla, ?zmir, Turkey, in March 2001 and 2002. By applying discrete Hilbert transform filter, the instantaneous amplitude, phase and frequency are found, and characterization of wind speed is accomplished. Authors have also tried to estimate the hourly wind data using daily sequence by Hilbert transform technique. Results are varying. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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Hannele Holttinen 《风能》2005,8(2):197-218
The variations of wind power production will increase the flexibility needed in the system when significant amounts of load are covered by wind power. When studying the incremental effects that varying wind power production imposes on the power system, it is important to study the system as a whole: only the net imbalances have to be balanced by the system. Large geographical spreading of wind power will reduce variability, increase predictability and decrease the occasions with near zero or peak output. The goal of this work was to estimate the increase in hourly load‐following reserve requirements based on real wind power production and synchronous hourly load data in the four Nordic countries. The result is an increasing effect on reserve requirements with increasing wind power penetration. At a 10% penetration level (wind power production of gross demand) this is estimated as 1·5%–4% of installed wind capacity, taking into account that load variations are more predictable than wind power variations. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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In wind integration studies, sub‐hourly, load synchronous wind data are often preferable. These datasets can be generated by a hybrid approach, combining hourly measurements or output from meteorological models with a stochastic simulation of the high‐frequency fluctuations. This paper presents a method for simulating aggregated intra‐hourly wind power fluctuations for a power system, taking into account the time‐varying volatility seen in measurements. Some key elements in the modelling were transformations to stationarity, the use of frequency domain techniques including a search for appropriate phase angles and an adjustment of the resulting time series in order to get correct hourly means. Generation data from Denmark and Germany with 5 and 15 min temporal resolution were used for training models. It is shown that the distribution and non‐stationarity of simulated deviations from hourly means closely follow those of measurements. Power spectral densities and step change distributions agree well. Of particular importance is that the results are good also when the training and objective power systems are not the same. The computational cost is low in comparison with other approaches for generating high‐frequency data. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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风力发电机组并网控制与仿真分析 总被引:3,自引:2,他引:3
用仿真方法研究了基于双馈异步发电机的风力发电机组的并网过程,分析了不同因素对发电机并网过程的影响。针对使风力发电机并网时可能产生较大冲击的各种因素,充分利用双馈感应发电机转子励磁的特点,提出了抑制和消除冲击的措施,以实现风力发电机组的快速、平稳并网。 相似文献