基于分段支持向量机的风电机组理论功率计算研究

结合风电机组功率曲线特性与支持向量机学习方法,建立基于分段支持向量机的风电机组理论功率计算模型。研究结果表明,该模型计算精度无论是在单机理论功率计算还是全场理论功率计算方面都要高于目前已有方法。在得到高精度理论功率的基础上,提出一个新的机组性能评价指标——出力可提高系数,该指标能够科学地反映机组设备的运行状态与质量,可为实现风场精细化管理提供依据。     

数据驱动风电机组偏航误差在线智能识别研究

针对不同风速下风向仪动态特性、风轮尾流、风向仪安装误差等因素导致的风电机组偏航误差问题,文章采用基于运行数据驱动的风电机组偏航误差方法进行在线智能识别。该方法通过改进DBSCAN聚类方法剔除过度离群数据,采用移动最小二乘法拟合“风速-功率-偏航误差”特性曲面,识别出不同风速下的偏航误差曲线,结合在线运行数据采集,可以实现不同风速下偏航误差的动态识别和持续矫正。算例分析表明,与偏航误差设定值相比,在有限数据下识别的偏航误差的识别结果较为准确,且识别误差在合理范围内。该方法的应用能够更为精确识别不同风速下风电机组偏航误差,进一步提高风电机组发电效率。     

风电机组实际运行功率曲线影响因素分析

本文对风电机组在运行过程中形成的实际运行功率曲线的主要影响因素进行分析,如:气象和环境条件、风电机组排列、对风偏差、机型、统计方法及采样修正等,从而阐述了标准功率曲线(合同功率曲线)与实际运行功率曲线产生偏差的原因,以此消除从业人员在风电机组功率特性曲线的认知方面存在的诸多误解,从而减少在风电场运营和质保交机时可能产生的不必要的纠纷。     

基于实时功率曲线的风电机组出力特性研究

基于实时功率曲线对风电机组出力特性进行分析,主要通过采集风电机组风速、功率、可靠性状态、大气压力、环境温度等历史数据进行过滤修正,计算出能够反映风电机组真实出力情况的实时功率曲线,并与出质保检测功率曲线进行对比,最后结合功率一致性系数对风电机组出力特性进行评价。找出性能下降比较严重的风电机组并及时整改,进而提高风电机组的发电能力。该方法不仅能够在线评价风电机组的性能优劣,且适用于各类型风电机组,具有广阔的应用前景。     

基于变距系统的风电机组并网运行特性的研究

依据风电机组的变桨距控制原理和风电机组的运行特性,建立了转速环和功率环控制的风电机组变桨距控制系统,结合双馈风电机组各部分数学模型,在PSCAD/EMTDC中搭建了风电机组的并网仿真模型。对不同风速段湍流风况条件下的风电机组并网运行特性进行仿真,实现了不同运行阶段下风电机组运行特性的优化控制,并在此基础上分别仿真了阵风干扰和电网故障扰动下风电机组的动态运行特性。仿真结果分析表明,双环变桨距控制系统可以较好地优化风电机组的功率输出特性,在电网发生故障时桨距角的快速动作也可以有效地抑制故障暂态响应的进一步恶化,有利于电网的迅速恢复。     

基于性能可靠性的风电机组功率曲线评定新方法

针对在实际风电机组验收过程中基于功率曲线的考核评估非常困难的问题,利用中央监控系统的机组运行数据,进行了运行功率曲线的测量,并基于性能可靠性理论,根据制造商承诺功率曲线性能,构建了基于性能可靠度的功率曲线评估方法.利用该方法对北方某风电场5台机组的功率曲线进行了评估.结果表明:5台机组中,6号机组的可靠性最高,4号机组的可靠性最差;该方法评估准确、简单实用,为工程中功率曲线的评价提供了参考.     

基于输出功率波动性的风电机组性能分析方法

输出功率特性是反映风电机组性能的主要指标之一,利用中央监控系统记录的运行数据,提出了3种不同的基于输出功率波动性机组性能分析方法。针对不同型号的机组,在测量机组动态功率曲线的基础上,构建基于功率曲线变异的输出性能分析模型;针对单台机组提出了基于风速和功率方差系数相关性的性能分析模型;针对单台机组运行在不同风速下,提出了基于分段风速的输出性能的分析方法。最后,以2个风电场的机组8个月的运行数据,对提出的机组分析性能方法进行验证,结果表明,文章提出的方法能够有效的分析风电机组的性能。     

基于机组来流等效风速计算的风电机组功率曲线修正

风电场功率曲线为工程中常用来描述机舱风速和输出功率之间关系的曲线,与厂商提供的理论功率曲线存在一定的差异。文中根据机舱测风仪的测风误差,提出了一种利用风电机组运行参数来反向迭代计算来流等效风速,拟合其与机舱风速的函数关系,并对理论功率曲线进行修正得到的机舱风速-功率曲线的方法。通过某电站的运行数据来推导来流风速,拟合来流风速与机舱风速间关系,并修正原功率曲线得到机舱风速-功率实际运行曲线,再将得到的机组功率指令来指导机组发电,从而降低机舱风速与来流等效风速存在偏差的影响,提高风电机组的发电效率。     

基于改进决策树的多变量功率曲线建模方法

为提高风电机组功率曲线的建模精度,利用偏互信息(PMI)方法对影响机组风能捕获的因素进行全面分析,并选取多参数作为输入变量。利用随机梯度提升回归树(SGBRT)算法,实现多变量下的功率曲线建模。结合某风电场1.5 MW机组数据采集与监视控制系统(SCADA)的实测数据,对所提出的功率曲线建模方法进行验证。结果表明:与现有功率曲线建模方法相比,采用SGBRT算法得到的功率曲线模型可更精确地预测风力机的功率特性,且预测误差最小。     

基于SRTM数据的地形测量方法研究

风电场地形是影响风电机组功率运行特性指标最主要的因素之一。本文根据国际电工委员会颁布的IEC 61400-12-1标准,基于SRTM地形数据与MATLAB软件,运用PCA(Principal Components Analysis)方法拟合出过风电机组塔基中心的最佳平面,计算出风电机组20倍叶轮直径范围内的地形坡度及高度偏差,并给出了工程实例的计算,为风电机组功率特性测试场地评估提供了相关参考。     

基于LabVIEW的离网型风力发电机风速-功率特性研究

通过对离网型风力发电机实际运行状态及气象情况的监测,绘制了风速-功率散点图.利用最大似然估计法对风机输出功率曲线进行拟合,结果表明:七次多项式拟合结果最逼近实际工况;二次多项式拟合曲线精度稍差,但表达式简单明了,可快速预测风力发电机发电量.此外,通过对风力发电机发电量的实际值、理论功率曲线预测值以及利用最大似然估计法拟合得到的功率曲线的预测值的对比,结果表明:风力发电机生产厂商提供的曲线只能反映其稳态的风速-功率关系,用来预测风力发电机发电量还存在较大误差;利用最大似然估计法拟合得到的功率曲线预测的风力发电机发电量误差明显偏小.     

风电机组振动数据分析与偏航校正

风电机组运行数据能够反映各系统之间的相关性和机组运行中存在的问题。为了判断机组发电效率低的原因,本文根据机舱振动加速度数据提出假定并通过计算分析风速功率曲线和偏航误差角度对应关系。现场检查结果表明,该机组偏航存在45°误差并导致振动异常,与理论推算误差角度44.6°相符。     

风力发电液力机械调速装置系统动态特性研究

为实现2 MW风电机组的高效传动,通过实验方法测得导叶可调式双涡轮液力变矩器输出特性曲线,计算得到不同开度下涡轮力矩与涡轮转速的三次项系数关系式,推导风力发电液力调速系统行星轮系的数学模型,设计了模糊自整定PID控制器的控制系统,并对风电机组进行了动态仿真和实验对比研究。结果表明:数值计算功率数值均大于实验值,风速小于5 m/s时绝对误差较小,风速大于5 m/s时进入正常发电工况,最大误差为7%。     

Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy

A power curve conventionally represents the relationship between hub height wind speed and wind turbine power output. Power curves facilitate the prediction of power production at a site and are also useful in identifying the significant changes in turbine performance which can be vital for condition monitoring. However, their accuracy is significantly influenced by changes in air density, mainly when the turbine is operating below rated power. A Gaussian process (GP) is a nonparametric machine learning approach useful for power curve fitting. Critical analysis of temperature correction is essential for improving the accuracy of wind turbine power curves. The conventional approach is to correct the data for air density before it is binned to provide a power curve, as described in the IEC standard. In this paper, four different possible approaches of air density correction and its effect on GP power curve fitting model accuracy are explored to identify whether the traditional IEC approach used for air density correction is most effective when estimating power curves using a GP. Finding the most accurate air density compensation approach is necessary to minimize GP model uncertainty.     

双馈风力发电系统最大风能追踪控制的研究

在分析了风力机功率特性和DFIG运行特性的基础上,通过对双馈机转速控制进行最大风能追踪具体过程的深入研究,提出了一种基于最大风能追踪的双馈电机有功、无功功率的解耦控制方法。建立了基于发电机定子磁链定向矢量控制的双馈风力发电系统最大风能追踪系统模型,并利用PSCAD/EMTDC对其进行仿真,结果验证了控制策略的正确性。     

基于改进支持向量机的多能源电力系统中储能容量规划及运行模型

研究多能源电力系统中储能装置的定容及运行,有利于减小功率波动,降低对电网的冲击,提高电能质量。以青海省海西千万瓦级可再生能源基地为例,首先根据光伏电站和风电场的历史数据分析了两种新能源发电系统的出力特性,在此基础上建立了支持向量机模型,对新能源电站的输出功率进行了短期预测。根据光伏电站和风电场的出力预测误差,建立了ARMA误差预测模型,进一步修正了光伏电站和风电场的预测曲线,最后根据出力预测曲线的功率谱确定了储能系统的容量及出力曲线。研究成果可为新能源并网提供技术支持。     

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.     

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。     

Potential of power gain with improved yaw alignment

One of the primary criteria for extracting energy from the wind using horizontal axis upwind wind turbines is the ability to align the rotor axis with the dominating wind direction. The conventional way of estimating the direction of the incoming flow is by using transducers placed atop the nacelle and downwind of the rotor. Recent studies have suggested methods based on advanced upwind measurement technologies for estimating the inflow direction and improving the yaw alignment. In this study, the potential of increased power output with improved yaw alignment is investigated by assessing the performance of a current measurement and yaw control system. The performance is assessed by analyzing data containing upwind wind speed and direction measurements from a met mast, and yaw angle and power production measurements from an operating offshore wind turbine. The results of the analysis indicate that the turbine is operating with a wind speed‐dependent yaw error distribution. The theoretical annual energy production loss due to the yaw error distribution of the existing system is estimated to approximately 0.2%. Copyright © 2014 John Wiley & Sons, Ltd.     

Wind turbine power curve modelling using artificial neural network

Technical improvements over the past decade have increased the size and power output capacity of wind power plants. Small increases in power performance are now financially attractive to owners. For this reason, the need for more accurate evaluations of wind turbine power curves is increasing. New investigations are underway with the main objective of improving the precision of power curve modeling. Due to the non-linear relationship between the power output of a turbine and its primary and derived parameters, Artificial Neural Network (ANN) has proven to be well suited for power curve modelling. It has been shown that a multi-stage modelling techniques using multilayer perceptron with two layers of neurons was able to reduce the level of both the absolute and random error in comparison with IEC methods and other newly developed modelling techniques. This newly developed ANN modeling technique also demonstrated its ability to simultaneously handle more than two parameters. Wind turbine power curves with six parameters have been modelled successfully. The choice of the six parameters is crucial and has been selected amongst more than fifty parameters tested in term of variability in differences between observed and predicted power output. Further input parameters could be added as needed.