提升山地风电机组运行质量的策略研究

文章分析了风电机组运行过程中的各种指标,提出了影响风电机组运行质量的关键指标,针对如何提升山地风电机组关键指标提出了应对策略,并对提升机组功率曲线、降低机组故障率进行了应用分析,对提升风电机组运行质量有着重要的意义.     

风电机组的功率曲线验证方法研究

功率曲线是风电机组发电能力的重要指标。本文讨论了功率曲线验证的必要性,并且提出了一种利用实测功率曲线与年发电量的相关性来考核厂家提供功率曲线是否达标的方法。以典型风电机组为例进行了研究分析。     

风电机组功率曲线建模方法对比研究

风电机组功率曲线是风电机组重要的性能指标,表征了机组的实际运行状态。准确的实测风电功率曲线可以为风电机组性能评估、风电功率曲线监测、风电功率预测、风电场数值建模等工作提供重要的参考依据。但采用耗时的功率曲线建模方法会花费大量的建模时间,从而影响建模效率。文章从功率曲线建模的数据筛选和功率曲线拟合入手,选取耗时较短的二维核密度估计模型筛选风速功率散点集中区域内的正常运行数据,并选用5种功率曲线拟合方法对正常风速功率数据进行拟合。5种模型的建模精度和建模效率对比分析表明,多项式拟合方法原理简单,拟合速度最快,且拟合精度较高,比较适用于实际功率曲线的建模工作。     

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。     

风切变对风电机组测试功率曲线及发电量的影响

以2 MW风电机组为研究对象,评估了风切变效应对输出功率及年发电量的影响。用三级Taylor展开式描述风切变指数近似模型,通过模型分析了风速、风电机组结构参数、风切变之间的关系。通过现场试验,测试并计算了不同风切变条件下风电机组的功率曲线。结合试验场地测风塔年风频数据,分析了风切变对机组年发电量的影响。结果表明：当风切变指数大于0.25时,风电机组的功率曲线及发电量降低较为明显。     

边界层气象对风电机组功率特性的影响研究

边界层气象因素对运行过程中的风电机组性能和表现具有重要影响。文章利用激光雷达设备对某大型风电场开展了气象观测,针对不同湍流、风切变、日变化和降雨情况下风电机组的功率特性进行了研究。研究结果表明:高湍流在切入风速和额定风速左右会提升或降低机组的功率曲线,并增大输出功率的离散性;高切变在切入风速和额定风速左右均会提升机组的功率曲线,并减小输出功率的离散性;边界层的湍流和风切变等气象要素存在显著的日变化规律,并影响风电机组的功率曲线和输出功率的离散性,表现出日夜不同;降雨天气与非降雨天气相比,总体上提升了机组的功率曲线,并增大了输出功率的离散性。文章的研究结果可为风电项目评估发电量、风电场功率预报等工作提供参考。     

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。     

风电机组的功率模糊控制系统研究

变桨距风电机组是一个高阶、非线性、强耦合、多变量时变的系统,其控制系统是综合性控制系统。在额定风速以上采用功率反馈的模糊控制策略,通过对桨距角的控制,改变气流对叶片的攻角,使风力机吸收的风能在一个相对的稳定值,从而实现发电机恒功率输出。仿真结果表明,模糊控制方法更具优越性,在风力发电系统中能取得较好的控制效果,系统具有较强的抗扰性和快速性。     

风电机组叶片音视频监测系统应用研究

风力发电作为重要的一种发电方式,近几年发展越来越快。风电机组是由多个大部件组成,叶片作为首先受载的大部件,同时也是风电机组最重要的部位,叶片损伤会对机组性能及安全运行带来极大的影响。本文研究叶片的全方位监测方法,采用音频与视频相结合的方式,通过音频特征数据分析及图像识别算法,发现叶片表面的损伤,通过对三组叶片的差异性对比以及机器学习算法,能够有效识别叶片表面损伤问题,对叶片主动监测预警具有重要意义。     

基于Wilson法风力机叶片设计及试验研究

基于MATLAB平台,采用Wilson方法设计了1台300 W水平轴风力机,通过筛选选择某S翼型进行叶片设计,并对其气动性能进行了计算。计算结果表明,S翼型风轮有效尖速比范围较宽,功率系数CP值在0.3以上的区域所对应的尖速比λ为4¹0.5,整体的功率系数变化平缓;最大推力系数CT在高尖速比时变化平稳;有效转矩系数CM为310.5,整体的功率系数变化平缓;最大推力系数CT在高尖速比时变化平稳;有效转矩系数CM为3¹2.3,S翼型叶片气动性能较好。自制风力机样机在低速风洞中进行试验,试验结果表明,在风速为412.3,S翼型叶片气动性能较好。自制风力机样机在低速风洞中进行试验,试验结果表明,在风速为4¹4 m/s时,与市场上某300 W传统翼型风力机相比,S翼型风力机功率平均提高了30.76%,尤其在风速为414 m/s时,与市场上某300 W传统翼型风力机相比,S翼型风力机功率平均提高了30.76%,尤其在风速为4⁶ m/s时,S翼型风力机功率提高较大,可以更好地利用中低风速。通过计算和试验研究可知,该S翼型适用于小型风力机叶片的设计。     

Optimum aerodynamic design for wind turbine blade with a Rankine vortex wake

This paper presents a model to optimize the distribution of chord and twist angle of horizontal axis wind turbine blades, taking into account the influence of the wake, by using a Rankine vortex. This model is applied to both large and small wind turbines, aiming to improve the aerodynamics of the wind rotor, and particularly useful for the case of wind turbines operating at low tip-speed ratios. The proposed optimization is based on maximizing the power coefficient, coupled with the general relationship between the axial induction factor in the rotor plane and in the wake. The results show an increase in the chord and a slightly decrease in the twist angle distributions as compared to other classical optimization methods, resulting in an improved aerodynamic shape of the blade. An evaluation of the efficiency of wind rotors designed with the proposed model is developed and compared other optimization models in the literature, showing an improvement in the power coefficient of the wind turbine.     

风特性对风力发电机组输出功率的影响

为了准确研究不同类型的风速对并网风电机组输出功率的影响,建立了并网风力发电机模型和不同类型风速的模型。在不同类型风速的扰动下,对异步风电机输出功率的波动进行了仿真分析;针对引起功率振荡最严重的阵风,进行了不同频率的阵风扰动下风电机组功率振荡的比较,对阵风扰动下风电机组间的相互影响进行了仿真分析。结果表明,在相同幅值的扰动下,阵风引起的风电机组功率振荡最严重,机组功率振荡情况与阵风扰动的频率有关,单台机组在阵风扰动下产生的振荡对其他机组也会产生一定的影响。     

风轮尺寸与旋向对双风轮风力机功率特性的影响分析

为掌握双风轮风力机风轮尺寸与旋向对其功率特性的影响规律,文章建立了双风轮风力机气动特性分析模型,并与美国国家能源部可再生能源实验室的实验结果进行了对比,计算分析了双风轮尺寸和旋向对风力机功率特性的影响规律。结果表明:当风速为10 m/s时,设计的双风轮风力机比单风轮双叶片风力机输出功率提升了84.9%;随着风轮半径增大,双风轮风力机输出总功率逐渐增加;当前、后两风轮反向旋转时,双风轮风力机前风轮大后风轮小的布局可获得更高的输出功率,且增幅随着后风轮半径增大先减小后增大,最大增幅为5.3%;除前、后两风轮半径相同的情形之外,双风轮风力机前、后两风轮同向旋转时输出总功率更大。     

Reactive power capability of a wind turbine with doubly fed induction generator

The aim of the work is to derive a steady state PQ‐diagram for a variable speed wind turbine equipped with a Doubly Fed Induction Generator. Firstly, the dependency between optimal rotor speed and wind speed is presented. Secondly, the limitations in reactive power production, caused by the rotor current, the rotor voltage and the stator current are derived. Thirdly, the influence of switching from Δ to Y coupling of the stator is investigated. Finally, a complete PQ diagram for a wind turbine is plotted. It is concluded that the limiting factor regarding reactive power production will typically be the rotor current limit, and that the limit for reactive power absorption will be the stator current limit. Further, it is concluded that the rotor voltage will only have a limiting effect at high positive and negative slips, but near the limitation, the reactive power capability is very sensitive to small changes in the slip. Copyright © 2007 John Wiley & Sons, Ltd.     

风力发电机风轮与发电机匹配特性的试验研究

为了提高风力发电机的输出性能,针对离网小型风力机的风轮能量转换系统和发电机系统的性能进行了研究。通过对两副风轮、两台发电机进行交叉组合试验,分别采集了尖速比为3～8、风速为7～13 m/s时风力发电机的功率特性,同时还采集了发电机在不同工况下的温度场、扭矩、功率等参数,选出输出特性较好的发电机和风轮,然后将其组合,对其输出特性进行研究,并测试分析了整机的振动特性。寻找影响发电机系统性能及发电机与风轮系统匹配的相关规律及有机结合点。研究结果表明,风轮和发电机组合后的整体性能不是由单一因素决定的,而是由叶片翼型及安装方式、发电机的结构和技术参数等因素共同作用产生的综合效果,发电机的影响尤为明显。     

Using neural networks to estimate wind turbine power generation

This paper uses data collected at Central and South West Services Fort Davis wind farm (USA) to develop a neural network based prediction of power produced by each turbine. The power generated by electric wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to perform this prediction for diagnostic purposes-lower-than-expected wind power may be an early indicator of a need for maintenance. In this paper, characteristics of wind power generation are first evaluated in order to establish the relative importance for the neural network. A four input neural network is developed and its performance is shown to be superior to the single parameter traditional model approach     

基于叶素理论的风力机组建模与仿真

基于叶素理论建立了风力发电机组空载状况下的数学物理模型,以攻角为控制对象设计控制器,在此基础上,以Matlab/Simulink为工具,建立了系统仿真模型,采用"试凑法"选择PI控制器的参数,通过设定风速分析了风力发电机组的运行特性,仿真结果验证了理论分析的正确性。该研究对控制器的设计具有参考价值。     

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

Wind energy uptake in South Africa is significantly increasing both at the micro‐ and macro‐level and the possibility of embedded generation cannot be undermined considering the state of electricity supply in the country. This study identifies a wind hotspot site in the Eastern Cape province, performs an in silico deployment of three utility‐scale wind turbines of 60 m hub height each from different manufacturers, develops machine learning models to forecast very short‐term power production of the three wind turbine generators (WTG) and investigates the feasibility of embedded generation for a potential livestock industry in the area. Windographer software was used to characterize and simulate the net output power from these turbines using the wind speed of the potential site. Two hybrid models of adaptive neurofuzzy inference system (ANFIS) comprising genetic algorithm and particle swarm optimization (PSO) each for a turbine were developed to forecast very short‐term power output. The feasibility of embedded generation for typical medium‐scale agricultural industry was investigated using a weighted Weber facility location model. The analytical hierarchical process (AHP) was used for weight determination. From our findings, the WTG‐1 was selected based on its error performance metrics (root mean square error of 0.180, mean absolute SD of 0.091 and coefficient of determination of 0.914 and CT = 702.3 seconds) in the optimal model (PSO‐ANFIS). Criteria were ranked based on their order of significance to the agricultural industry as proximity to water supply, labour availability, power supply and road network. Also, as a proof of concept, the optimal location of the industrial facility relative to other criteria was X = 19.24 m, Y = 47.11 m . This study reveals the significance of resource forecasting and feasibility of embedded generation, thus improving the quality of preliminary resource assessment and facility location among site developers.