福建莆田石城风电场风电机组选型研究

由于风力发电设备的投资在风电场建设投资中占有相当大的比重,风电机组选型是风电场设计中的主要工作之一。结合福建莆田石城风电场的情况,从产品市场供应、技术特点、单机容量选择、技术参数比较、发电量和度电成本比较等几个方面对机组选型进行了研究．研究方法对其他风电场设计具有一定的参考和借鉴价值。     

一种评价风电场设计水平的新方法

提出了一种独立于当地风资源、基于实际设计水平来评价风电场设计水平的新方法。根据影响发电量的主要设计因素,引入衡量风电机组的选型和布置的3个新指标:风电场发电效率、风电机组容量系数和风电机组布置系数,并推导出这3个系数的表达式。提出的3个新指标具有明确的物理意义,可以定量评价风电场风电机组选型和布置对风电场设计水平的影响。最后对两个实际风电场进行了计算和分析,所得结果的正确性得到风电场实际运行调研和后评价的验证。该方法不仅提出了较全面的对风电场设计水平的评价方法,而且可以进行量化评分,对风电场的设计具有重要的理论意义和经济价值。     

风电场风力发电机组优化选型

基于蒙特卡罗方法建立风力发电机组的概率性模型,该模型充分考虑了风能随机性和发电设备被迫停运等随机性因素,能准确估算风力发电机组的年发电量、容量系数等经济指标;并对各种待选机组进行技术经济分析,实现机组优化选型。文中结合算例,研究风电机组参数对容量系数的影响,选择与实际风电场相匹配的风电机组。算例表明这种方法是可行的,具有实用价值。     

风向对广东海上风电场风机布置的影响

引入一个包含20台4 MW风力发电机组,风机布置采用规则几何构型的海上风电场理论模型,设计了两大类共4个不同的风机阵列,根据1991-2010年广东近海区域MERRA再分析资料,从海面风向的季节变化、扇区划分方式变化以及风向频率分布变化等三个方面开展数值试验研究。结果表明:平行四边形阵列比矩形阵列更具灵活性,能够适应更复杂的风向季节性偏转;风机布置需要更加细致的风向扇区划分方式,传统的16个风向扇区划分方式难以适应风机阵列最佳朝向的选择与调整;风机布置方案比选需要考虑风向频率分布的年际变动,通过敏感性试验识别更具稳定性的风机阵列。     

风电场风机初步选型方法研究

市场上可供选择的风机种类众多,各类风机在性能、价格、维修及制造商服务等多方面都存在明显差异,因此在选择风机时有必要综合考虑多方面因素。鉴于工程上对风机作初步选型时采用的方法大多具有局限性,文章在确定影响风机选型的主要因素后提出一套风机初步选型方法,该方法根据拟建风电场的情况和设计人员的要求,综合考虑各因素后选出符合条件的风机。文章基于该选型方法将Visual Basic语言与Microsoft Access数据库相结合,开发出相应的选型系统,使整个选型过程更为方便、快捷。     

某近海风电场风机基础选型设计

目的  自2022年起,海上风电的国家补贴将全面退出。海上风电机组基础是风电机组的支撑结构,对海上风电场的安全运行起着至关重要的作用。在平价上网、“30·60”双碳目标和国家“十四五”能源规划等政策的指导下,合理地选择、设计海上风电机组基础,是海上风电场降本增效的有效手段。 方法  文章以某近海风电场风机基础选型设计为例,综合国内海上风电场的建设经验,进行基础型式比选;首先选择单桩基础、导管架基础和高桩承台基础3种基础型式进行初选,然后结合该近海风电场的海洋水文和地质条件,分析不同风机基础型式的适用水深及优缺点,从结构安全性、施工可行性、工期及工程经济性等方面进行了综合比选。 结果  研究表明：风机基础型式的选择与水深、土层地质条件、风电机组固有频率、施工安装设备能力、施工工期、工程造价等几个因素有关。单桩基础结构型式优良、施工可行、工期最短、经济性最优,优势明显。 结论  推荐该近海风电场风机基础采用单桩基础方案。     

近海重力式风机基础结构模糊选型优化

针对近海风电场风机基础结构设计时基础型式的选择涉及复杂因素较多,为降低主观因素影响,使基础选型更加科学合理,应用非结构性模糊决策理论及两级模糊优选模型,特别针对岩石海床地基,对某拟建近海风电场的重力式风机基础进行了模糊选型优化,通过对比分析计算结果确定了较满意的结构型式,表明文中介绍方法行之有效.     

Fuga程序在福建省海上风电场风机布置中的应用

结合福建省莆田平海湾海上风电场F区项目设计过程中的风机布置优化过程,初步研究Fuga程序在海上风电场的风机选型、风机布置优化及发电量计算等的快捷、高效应用,对福建省海上风电场设计及建设有较好的推广价值,可为今后设计、建设同类项目开拓思路,提供一定的借鉴。     

风电机组选型的技术经济比选

1引言风电机组选择是诸种因素、多指标综合优化的结果,首先需要对项目风资源进行详尽的论证,在比较机组发电能力等技术因素的基础上,综合考虑机组安全可靠性、设备价格及后期运营维护成本等。风力发电工程设计过程中,在各机型上网电量基础上进行经济效益比选,最终选取最优机型。     

海上风电场升压平台布置研究初探

分析了目前国内外海上风电场升压平台的发展现状,对海上变电站电气布置方案进行了研究分析。提出了海上变电站的功能区域划分以及布局的基本要求和原则。根据海上风电场的环境特点和运行要求,研究海上升压站设备选型的适用原则,并结合一个海上风电场升压站典型布置案例,对主要电气设备和配电装置在海上变电站布置优化提出了建议。     

海上风力发电机组基础的选择

介绍了海上风力发电的发展现状,结合海上采油平台形式,对海上风电机组采用的基础定义、基础类型及其选择进行了介绍。     

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd.     

风电场风电机组的接地设计

较系统地介绍了风电场风电机组对接地电阻的要求、接地设计思路及方法,并提供实际工程中接地网布置图实例作为参考。     

Adjustment of wind farm power output through flexible turbine operation using wind farm control

When the installed capacity of wind power becomes high, the power generated by wind farms can no longer simply be that dictated by the wind speed. With sufficiently high penetration, it will be necessary for wind farms to provide assistance with supply‐demand matching. The work presented here introduces a wind farm controller that regulates the power generated by the wind farm to match the grid requirements by causing the power generated by each turbine to be adjusted. Further, benefits include fast response to reach the wind farm power demanded, flexibility, little fluctuation in the wind farm power output and provision of synthetic inertia. Copyright © 2015 John Wiley & Sons, Ltd.     

基于CFO的海上风电场微观选址优化算法研究

海上风电场用海面积有限,尾流影响比陆上大,微观选址是其规划设计的关键技术。传统优化算法大多采用离散化变量,使得潜在解空间减少到有限个,难以达到最优化的效果。为了提高海上风电场微观选址优化效率,文章提出了一种基于中心引力优化(CFO)算法的海上风电场微观选址方法。该算法使用实数编码,通过将微观选址优化的变量假设为天体,各个天体之间相互作用,达到平衡的原理,具有可能得到全局最优解和效率高的优点。使用该算法对海上风电场微观选址优化进行仿真,并与现有方法比较。结果表明,所提出的算法得到的排布方式发电量最高,并具有优化精度高、速度快和优化排布较为均匀的特点。该研究结果可以为实际工程应用提供参考。     

新型海上风力发电及其关键技术研究

回顾国外海上风力发电场的发展,针对随着海水深度增加导致海上风力机成本急剧上升的矛盾,引入海上漂浮式风力机概念,并详细介绍其结构和特点,通过系统介绍海上漂浮式风力机组成部分和设计制造中的关键技术,最后得出海上漂浮式风机是一种潜力巨大的新型风力发电技术,值得进一步深入研究。同时,针对我国陆、海资源的具体情况,较为系统地提出了海上漂浮式风力机研究的需要关注的关键问题,指出了该研究所具有的巨大社会经济价值。     

Evaluation of the wind direction uncertainty and its impact on wake modeling at the Horns Rev offshore wind farm

Accurately quantifying wind turbine wakes is a key aspect of wind farm economics in large wind farms. This paper introduces a new simulation post‐processing method to address the wind direction uncertainty present in the measurements of the Horns Rev offshore wind farm. This new technique replaces the traditional simulations performed with the 10 min average wind direction by a weighted average of several simulations covering a wide span of directions. The weights are based on a normal distribution to account for the uncertainty from the yaw misalignment of the reference turbine, the spatial variability of the wind direction inside the wind farm and the variability of the wind direction within the averaging period. The results show that the technique corrects the predictions of the models when the simulations and data are averaged over narrow wind direction sectors. In addition, the agreement of the shape of the power deficit in a single wake situation is improved. The robustness of the method is verified using the Jensen model, the Larsen model and Fuga, which are three different engineering wake models. The results indicate that the discrepancies between the traditional numerical simulations and power production data for narrow wind direction sectors are not caused by an inherent inaccuracy of the current wake models, but rather by the large wind direction uncertainty included in the dataset. The technique can potentially improve wind farm control algorithms and layout optimization because both applications require accurate wake predictions for narrow wind direction sectors. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

Optimal turbine spacing in fully developed wind farm boundary layers

As wind farms become larger, the asymptotic limit of the ‘fully developed’, or ‘infinite’, wind farm has been receiving an increased interest. This limit is relevant for wind farms on flat terrain whose length exceeds the height of the atmospheric boundary layer by over an order of magnitude. Recent computational studies based on large eddy simulation have identified various mean velocity equilibrium layers and have led to parameterizations of the effective roughness height that allow the prediction of the wind velocity at hub height as a function of parameters such as wind turbine spacing and loading factors. In the current paper, we employ this as a tool in making predictions of optimal wind turbine spacing as a function of these parameters, as well as in terms of the ratio of turbine costs to land surface costs. For realistic cost ratios, we find that the optimal average turbine spacing may be considerably higher than that conventionally used in current wind farm implementations. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm

A modeling framework is proposed and validated to simulate turbine wakes and associated power losses in wind farms. It combines the large-eddy simulation (LES) technique with blade element theory and a turbine-model-specific relationship between shaft torque and rotational speed. In the LES, the turbulent subgrid-scale stresses are parameterized with a tuning-free Lagrangian scale-dependent dynamic model. The turbine-induced forces and turbine-generated power are modeled using a recently developed actuator-disk model with rotation (ADM-R), which adopts blade element theory to calculate the lift and drag forces (that produce thrust, rotor shaft torque and power) based on the local simulated flow and the blade characteristics. In order to predict simultaneously the turbine angular velocity and the turbine-induced forces (and thus the power output), a new iterative dynamic procedure is developed to couple the ADM-R turbine model with a relationship between shaft torque and rotational speed. This relationship, which is unique for a given turbine model and independent of the inflow condition, is derived from simulations of a stand-alone wind turbine in conditions for which the thrust coefficient can be validated. Comparison with observed power data from the Horns Rev wind farm shows that better power predictions are obtained with the dynamic ADM-R than with the standard ADM, which assumes a uniform thrust distribution and ignores the torque effect on the turbine wakes and rotor power. The results are also compared with the power predictions obtained using two commercial wind-farm design tools (WindSim and WAsP). These models are found to underestimate the power output compared with the results from the proposed LES framework.