计及随机波动风速、风向的风电场建模方法研究

提出风电场建模方法建立风电场随机模型,对风电场运行特性进行仿真,为实现大规模风力发电的可预测、可控制目标服务。通过对风电场等值模型与详细模型的仿真比较,验证建模方法的合理性,并得出在研究风电场动态特性及其对电网影响时应考虑风速、风向的随机波动建立风电场模型。     

大型风电场失速型机组等值建模的研究

对于风电场中失速型机组的多机等值,采用异步发电机的机电暂态模型求解发电机组的等值电气参数,利用基于传递函数概念的参数辨识方法及最小二乘法求解发电机组的动态等值参数。利用系统等值得结果对一实例进行仿真,结果表明了等值方法的有效性和正确性,为今后研究风电场与电网之间的相互影响提供了良好的模型基础。     

风电场不同等值模型的仿真研究

以含笼型异步发电机组的并网风电场为例,在分析单机异步风力发电机动态模型的基础上,研究了风电场容量加权单机等值、降阶变尺度多机等值、参数变换单机等值以及改进加权单机等值模型和方法.针对风电场机组参数完全相同和不同的两种算例,利用Matlah/Simulink平台建立了风电场不同等值模型,对风速扰动和风电场出口处发生三相短...     

大规模并网型风电场等值建模研究现状

风电场等值模型的建立有助于对含有大规模风电接入的电网进行稳态运行以及各种稳定性问题的分析研究。介绍了风电场等值建模的基本思想,基于国内外关于大规模并网型风电场等值建模的研究现状,对风电场稳态和动态的各种等值建模法进行了简要的分析和综述。     

基于改进D-K聚类算法的直驱型风电场动态等值建模

研究永磁同步发电机(PMSG)的低电压穿越(LVRT)特性,提出一种基于改进D-K聚类算法的直驱型风电场等值建模方法。首先,根据风电场内各台PMSG卸荷电路的导通情况对风电场进行首次分群。其次,将卸荷电路未导通的PMSG故障期间的机端电压值作为分群指标,应用改进D-K聚类算法对风电场进行聚类等值。该算法解决了传统K-均值聚类算法k值需提前给定和依赖于初始聚类中心的问题。最后,以某实际风电场为例进行仿真分析,结果表明该等值模型与传统等值模型相比能更准确地反映直驱型风电场的动态和暂态运行特性。     

双馈风电机组的建模仿真及其等值方法研究

文章分析了双馈风力发电机组的数学模型及控制模型,基于PSCAD/EMTDC平台搭建了双馈风力发电机组仿真模型,以阵风和渐变风为例,对风力发电机组并网运行端口的稳态特性和故障特性进行仿真,其结果实现定子侧有功、无功解耦控制及电压的恒定,验证了所建模型的正确性。在考虑尾流效应的情况下,研究了不同类型的双馈风电机组等值思路,搭建了等值模型,对其等值前后的稳态、暂态特性进行对比分析,结果表明了该等值方法的有效性,为大规模并网型双馈机组风电场进一步研究提供了有利条件。     

基于改进猴群算法的山地风电场建模研究

根据风电场等值建模理论,利用风电场的详细模型,提出了一种基于改进猴群算法的山地风电场建模方法,并在Matlab/Simulink环境下建立一个9 MW的小型风电场进行了仿真实验。通过三种风速下的仿真结果表明,基于改进猴群算法的单机等值模型和详细模型具有基本一致的运行特性,可以更加简单方便地得到风电场的模型,这为大型山地风电场的等值建模提供了基础。     

直驱式风电场并网动态等值研究

随着直驱式风力发电机在电网中的比例增加,研究其精确的动态等值模型越来越重要。根据直驱式风力发电机的输出特性,提出了基于风速分群的多机等值方法。在等值计算中,考虑了直驱式风电机组并网时变压器和集电线路对等值效果的影响,并计及了尾流效应对风机输入风速的影响。所提等值方法适合于直驱式风电场并网的分析计算,具有实际工程的应用价值。     

含变速双馈风电机组风电场的等值问题

在研究含变速双馈风电机组的风电场对电网的影响时,需要建立合理的风电场模型.文章介绍了大型风电场的等值建模的主要特点,探讨了含变速双馈风电机组的风电场等值方法和在等值过程中应注意的问题,为今后变速双馈风电机组在大型并网风电场中的应用提供参考.     

基于改进遗传KM聚类算法的风电场机群划分方法

为准确分析风电场的动态特性,借助同调等值法的思想,提出了一种基于改进遗传KM聚类算法的机群划分方法。此方法通过构造有效的适应度函数,结合K-means聚类算法和遗传聚类算法的优点,以实测风速数据为分群指标,对风电场进行机群划分。将同群风电机组等值为1台风电机组,建立风电场动态等值模型,并与传统单机等值模型和K-means等值模型进行了比较分析。以某风电场为例进行的仿真验证结果表明,采用所提方法建立的等值模型能够较为准确地反映风电场的动态响应特性,从而提高等值模型的精确性。     

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.     

Using nacelle‐based wind speed observations to improve power curve modeling for wind power forecasting

Wind power forecasting for projection times of 0–48 h can have a particular value in facilitating the integration of wind power into power systems. Accurate observations of the wind speed received by wind turbines are important inputs for some of the most useful methods for making such forecasts. In particular, they are used to derive power curves relating wind speeds to wind power production. By using power curve modeling, this paper compares two types of wind speed observations typically available at wind farms: the wind speed and wind direction measurements at the nacelles of the wind turbines and those at one or more on‐site meteorological masts (met masts). For the three Australian wind farms studied in this project, the results favor the nacelle‐based observations despite the inherent interference from the nacelle and the blades and despite calibration corrections to the met mast observations. This trend was found to be stronger for wind farm sites with more complex terrain. In addition, a numerical weather prediction (NWP) system was used to show that, for the wind farms studied, smaller single time‐series forecast errors can be achieved with the average wind speed from the nacelle‐based observations. This suggests that the nacelle‐average observations are more representative of the wind behavior predicted by an NWP system than the met mast observations. Also, when using an NWP system to predict wind farm power production, it suggests the use of a wind farm power curve based on nacelle‐average observations instead of met mast observations. Further, it suggests that historical and real‐time nacelle‐average observations should be calculated for large wind farms and used in wind power forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamic model of wind energy conversion systems with PMSG-based variable-speed wind turbines for power system studies

In order to study the impact of a wind farm on the dynamics of the power system, a significant issue is to develop appropriate equivalent models that allow characterizing the dynamics of all individual wind turbine generators (WTGs) composing the park. In this sense, with the advance of power electronics, direct-driven permanent magnet synchronous generators (PMSGs) have drawn increased interest to wind turbine manufacturers due to their advantages over other variable-speed WTGs. These include the possibility of multi-pole design with a gearless construction that offers slow speed operation and reduced maintenance since no brushes are used, elimination of the excitation system, full controllability for maximum wind power extraction and grid interface, and easiness in accomplishing fault-ride through and grid support. In this way, this paper presents a comprehensive dynamic equivalent model of a wind farm with direct-driven PMSG wind turbines using full-scale converters and its control scheme. The proposed simplified modelling is developed using the state-space averaging technique and is implemented in the MATLAB/Simulink environment. The dynamic performance of the wind farm and its impact on the power system operation is evaluated using the phasor simulation method.     

Aggregated dynamic model for wind farms with doubly fed induction generator wind turbines

As a result of increasing wind farms penetration in power systems, the wind farms begin to influence power system, and thus the modelling of wind farms has become an interesting research topic. Nowadays, doubly fed induction generator based on wind turbine is the most widely used technology for wind farms due to its main advantages such as high-energy efficiency and controllability, and improved power quality. When the impact of a wind farm on power systems is studied, the behavior of the wind farm at the point common coupling to grid can be represented by an equivalent model derived from the aggregation of wind turbines into an equivalent wind turbine, instead of the complete model including the modelling of all the wind turbines. In this paper, a new equivalent model of wind farms with doubly fed induction generator wind turbines is proposed to represent the collective response of the wind farm by one single equivalent wind turbine, even although the aggregated wind turbines operate receiving different incoming winds. The effectiveness of the equivalent model to represent the collective response of the wind farm is demonstrated by comparing the simulation results of equivalent and complete models both during normal operation and grid disturbances.     

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.     

Grid support of a wind farm with active stall wind turbines and AC grid connection

One of the main concerns in the grid integration of large wind farms is their ability to behave as active controllable components in the power system. This article presents the design of a new integrated power control system for a wind farm made up exclusively of active stall wind turbines with AC grid connection. The designed control system has the task of enabling such a wind farm to provide the best grid support. It is based on two control levels: a supervisory control level, which controls the power production of the whole farm by sending out reference signals to each individual wind turbine, and a local control level, which ensures that the reference power signals at the wind turbine level are reached. The ability of active stall wind farms with AC grid connection to control the power production to the reference power ordered by the operators is assessed and discussed by means of simulations. Copyright © 2005 John Wiley & Sons, Ltd.     

基于风电机组无功裕度预测的风电场无功分层控制策略

针对风电电压波动的问题,文章基于风电机组无功裕度预测,提出了一种风电场无功分层控制策略.该策略首先以并网点电压偏差和线路有功损耗最小为目标,使用二次规划算法在线实时求解最优并网电压,进而求解风电场无功参考值;其次,采用EWT-LSSVM预测算法进行风电功率预测,并提出预测功率校正方法实时修正预测功率,精确求解风电机组的...     

Centralised power control of wind farm with doubly fed induction generators

At the moment, the control ability of wind farms is a prime research concern for the grid integration of large wind farms, due to their required active role in the power system. This paper describes the on-going work of a research project, whose overall objective is to analyse and assess the possibilities for control of different wind farm concepts. The scope of this paper is the control of a wind farm made up exclusively of doubly fed induction generators. The paper addresses the design and implementation issues of such a controller and focuses on the ability of the wind farm control strategy to regulate the wind farm power production to the reference power ordered by the system operators. The presented wind farm control has a hierarchical structure with both a central control level and a local control level. The central wind farm control level controls the power production of the whole farm by sending out reference power signals to each individual wind turbine, while the local wind turbine control level ensures that the reference power signal send by the central control level is reached. The performance of the control strategy is assessed and discussed by means of simulations illustrated both at the wind farm level and at each individual wind turbine level.     

Statistical wind direction modeling for the analysis of large scale wind power generation

Understanding the effects of large‐scale wind power generation on the electric power system is growing in importance as the amount of installed generation increases. In addition to wind speed, the direction of the wind is important when considering wind farms, as the aggregate generation of the farm depends on the direction of the wind. This paper introduces the wrapped Gaussian vector autoregressive process for the statistical modeling of wind directions in multiple locations. The model is estimated using measured wind direction data from Finland. The presented methodology can be used to model new locations without wind direction measurements. This capability is tested with two locations that were left out of the estimation procedure. Through long‐term Monte Carlo simulations, the methodology is used to analyze two large‐scale wind power scenarios with different geographical distributions of installed generation. Wind generation data are simulated for each wind farm using wind direction and wind speed simulations and technical wind farm information. It is shown that, compared with only using wind speed data in simulations, the inclusion of simulated wind directions enables a more detailed analysis of the aggregate wind generation probability distribution. Copyright © 2016 John Wiley & Sons, Ltd.