并网双馈风电机组低电压穿越能力研究

详细分析了双馈风电机组LVRT功能的实现原理,并在电力系统仿真分析软件PSASP中建立双馈风电机组的LVRT功能模型,采用地理接线图直观地表示风电场外部系统发生短路故障瞬间对风电机组端电压的影响．并以我国某地区电网为例来分析在风电场接入方式不同的情况下系统短路故障对风电机组的影响。根据仿真结果给出风电机组LVRT能力的最低电压限值要求。最后提出了利用串联制动电阻来提高风电机组的LVRT能力的新方法。分析结果表明,串联制动电阻能够可观地提高风电机组的低电压穿越能力。具有较高LVRT能力的风电机组。可以节省一定的投资费用,在一定程度上降低了风电的上网电价。     

不同风电场模型对风电场电压的影响评估

目前,实际的电力系统仿真计算将风电场处理为一台风电机组。随着并入输电网的风电容量持续增加,仍按照一台风机等效对系统仿真计算造成的误差不容忽视,该误差能引起风电场内部保护装置的误动作。文章针对不同风电模型对风电场电压的影响做了详细比较,并给出了量化指标。经过试验仿真分析得出以下结论:不同风电场模型对风电场出口和并网点电压的影响不同,当恒速异步风电机构成的风电场采用一台风电机等效时,将会使风电场出口的相电压计算平均误差达到16.667%。因此,为保证仿真精度与风电场保护的正确动作,在对含风电场的电力系统进行仿真计算时,应将风电场处理为若干台风电机。     

电网超短期运营约束下风电随机波动风险评估及平抑措施

针对风电并网后其随机波动性会给电力系统带来极大风险的问题,根据某风电场的实际数据统计出风电场输出功率瞬时波动特性,设计了基于机组AGC运行约束的电力系统实时发电计划模型,采用风险价值（VaR）方法评估了不同风电机组容量下风电场出力瞬时波动下的运营损失,并以简化的某电网模型作为算例进行了验证,进而提出相应的措施以平抑风力波动给电力系统带来的风险。     

风电场的继电保护

大规模风电接人系统对电力系统电能质量的影响较大.风能的随机性和不可控性,使风电占系统容量的份额增大时,向系统提供的短路电流也越来越大,因此,风电保护配置对电网的影响也是重要的.文章对风电系统保护进行了论述,分析了风电对电网继电保护的影响,使用MATLAB的动态仿真工具SIMULINK、对包含风电场的单机无穷大电力系统发生联络线故障时进行动态仿真.通过分析双馈发电机不同故障类型下的故障电压、电流曲线,指出风电场应采用的适应性保护.     

风电机组振动监测系统对齿轮箱故障的检测与诊断

着重介绍了本特利内华达ADAPT.wind风电机组在线状态监测系统边带能量率的算法原理,并以在风电机组齿轮箱故障诊断中的应用实例,充分说明其对风电场运营业主提高风电机组管理水平和运营效率的有效性。     

恒速和双馈感应风电机的稳定性研究

随着并网风电容量的增大,风电在电力系统中比重的增加,为研究风力发电系统的稳定性,采用电力系统仿真软件DIgSILENT/PowerFactory对恒速和双馈感应两种异步风电机进行建模仿真,分析其在短路故障时不同风电机组及电气参数对系统恢复稳定的影响。结果表明:双馈感应风电机的故障动态响应比较敏感,具有明显优势。     

恒速和双馈感应风电机的稳定性研究

随着并网风电容量的增大,风电在电力系统中比重的增加,为研究风力发电系统的稳定性,采用电力系统仿真软件DIgSILENT/PowerFactory对恒速和双馈感应两种异步风电机进行建模仿真,分析其在短路故障时不同风电机组及电气参数对系统恢复稳定的影响。结果表明:双馈感应风电机的故障动态响应比较敏感,具有明显优势。     

基于风电机组可靠性的风电场平准化成本模型研究

考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。     

双馈变速风电机组低电压穿越控制

当系统中风电装机容量比例较大时,系统故障导致电压跌落后,风电场切除会严重影响系统运行的稳定性,这就要求风电机组具有低电压穿越（Low Voltage Ride Through,LVRT）能力,保证系统发生故障后风电机组不间断并网运行。分析了双馈风电机组LVRT原理和基于转子撬棒保护（crow-bar protection）的LVRT控制策略,在电力系统仿真分析软件DIgSILENT/Power Factory中建立了双馈风电机组模型及其LVRT控制模型,以某地区风电系统为例进行仿真计算,分析转子撬棒投入与切除策略及动作时间对实现机组LVRT的影响。     

低碳经济下含风储联合电力系统优化调度

从低碳经济角度建立了含高渗透率风电的风储联合电力系统优化调度模型。该模型以系统综合运行成本最小为目标,合理评估了常规火电机组运行成本、风电运行成本、储能运行成本及环境成本,并结合电池储能可变寿命特征,综合考虑了放电深度对储能运行成本的影响。以改进的IEEE RTS-96系统及某风电场历史出力数据为例,对含风储联合电力系统优化调度予以研究,结果表明大规模风储并网对电力系统低碳化、清洁化具有积极影响,含风储联合电力系统的优化调度与风电出力特性、风电并网渗透率等因素密切相关。     

Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

风电与燃气轮机互补发电系统发电成本分析

在采用风电场与小型燃气轮机组成的互补系统发电特性参数的基础上,详细分析了互补系统发电成本的构成和各自的计算方法。采用新疆达坂城风电场的风速数据,基于互补系统的发电特性参数和风电场与燃气轮机电站的发电成本构成,应用改进过的等额支付折算法,在当前的技术条件和价格下,计算了风电场子系统和燃气轮机电站子系统各自的折旧成本、燃料成本和运行维护成本,得到了整滚发电系统发电成本的计算方法,为在新疆地区实现这种互补发电系统提供经济分析基础。     

Quantification of power losses due to wind turbine wake interactions through SCADA,meteorological and wind LiDAR data

Power production of an onshore wind farm is investigated through supervisory control and data acquisition data, while the wind field is monitored through scanning light detection and ranging measurements and meteorological data acquired from a met‐tower located in proximity to the turbine array. The power production of each turbine is analysed as functions of the operating region of the power curve, wind direction and atmospheric stability. Five different methods are used to estimate the potential wind power as a function of time, enabling an estimation of power losses connected with wake interactions. The most robust method from a statistical standpoint is that based on the evaluation of a reference wind velocity at hub height and experimental mean power curves calculated for each turbine and different atmospheric stability regimes. The synergistic analysis of these various datasets shows that power losses are significant for wind velocities higher than cut‐in wind speed and lower than rated wind speed of the turbines. Furthermore, power losses are larger under stable atmospheric conditions than for convective regimes, which is a consequence of the stability‐driven variability in wake evolution. Light detection and ranging measurements confirm that wind turbine wakes recover faster under convective regimes, thus alleviating detrimental effects due to wake interactions. For the wind farm under examination, power loss due to wake shadowing effects is estimated to be about 4% and 2% of the total power production when operating under stable and convective conditions, respectively. However, cases with power losses about 60‐80% of the potential power are systematically observed for specific wind turbines and wind directions. Copyright © 2017 John Wiley & Sons, Ltd.     

Development of a comprehensive MPPT for grid‐connected wind turbine driven PMSG

This paper proposes a comprehensive MPPT method by which extraction of maximum power from wind turbine and its subsequent transfer through various power stages and final delivery to the connected grid are realized. In the proposed system, the operation of the wind turbine at its maximum efficiency point is maintained by control of grid‐tied inverter such that the shaft speed of the generator is set to result the desired optimum tip speed ratio of the turbine. The proposed comprehensive MPPT estimates the required DC link voltage for each wind speed using a unified system model, uses a loss factor to account for the system losses, and then controls the inverter to push the WT extracted maximum power into the grid. The comprehensive MPPT is developed and is validated in MATLAB/Simulink platform in a wide range of operating wind speed. The results ascertain that the wind turbine is made to operate at its maximum efficiency point for all wind speeds below the rated one.     

Insurance strategy for mitigating power system operational risk introduced by wind power forecasting uncertainty

The increasing penetration of wind power significantly affects the reliability of power systems due to its intrinsic intermittency. Wind generators participating in electricity markets will encounter operational risk (i.e. imbalance cost) under current trading mechanism. The imbalance cost arises from the service for mitigating supply-demand imbalance caused by inaccurate wind forecasts. In this paper, an insurance strategy is proposed to cover the possible imbalance cost that wind power producers may incur. First of all, a novel method based on Monte Carlo simulations is proposed to estimate insurance premiums. The impacts of insurance excesses on premiums are analyzed as well. Energy storage system (ESS) is then discussed as an alternative approach to balancing small wind power forecasting errors, whose loss claims would be blocked by insurance excesses. Finally, the ESS and insurance policy are combined together to mitigate the imbalance risks of trading wind power in real-time markets. With the proposed approach, the most economic power capacity of ESS can be determined under different excess scenarios. Case studies prove that the proposed ESS plus insurance strategy is a promising risk aversion approach for trading wind power in real-time electricity markets.     

基于多指标融合评价方法的风电机组优化选型辅助决策系统设计

应用科学的手段对风电机组有效的选型,对确保风电场经济效益提高、产能增加、机组可用系数和上网率提高、投资量和运维费用减少并实现风机实际运行值与理论设计值高度具有重要作用。建立了风电机组多指标融合评价指标体系和评价方法,并开发出了基于多指标融合评价方法的风电机组优化选型辅助决策系统,并在工程应用中起到了良好的社会效益和经济效益,为发电企业的风电机组优化选型起到了积极作用。     

Predictions of ice formations on wind turbine blades and power production losses due to icing

Prediction of ice shapes on a wind turbine blade makes it possible to estimate the power production losses due to icing. Ice accretion on wind turbine blades is responsible for a significant increase in aerodynamic drag and decrease in aerodynamic lift and may even cause premature flow separation. All these events create power losses and the amount of power loss depends on the severity of icing and the turbine blade profile. The role of critical parameters such as wind speed, temperature, liquid water content on the ice shape, and size is analyzed using an ice accretion prediction methodology coupled with a blade element momentum tool. The predicted ice shapes on various airfoil profiles are validated against the available experimental and numerical data in the literature. The error in predicted rime and glime ice volumes and the maximum ice thicknesses varies between 3% and 25% in comparison with the experimental data depending on the ice type. The current study presents an efficient and accurate numerical methodology to perform an investigation for ice‐induced power losses under various icing conditions on horizontal axis wind turbines. The novelty of the present work resides in a unified and coupled approach that deals with the ice accretion prediction and performance analysis of iced wind turbines. Sectional ice profiles are first predicted along the blade span, where the concurrence of both rime and glaze ice formations may be observed. The power loss is then evaluated under the varying ice profiles along the blade. It is shown that the tool developed may effectively be used in the prediction of power production losses of wind turbines at representative atmospheric icing conditions.     

基于改进网侧控制策略的半直驱风电系统FFRT研究

[目的]为改进半直驱风电系统的故障电压穿越（Flexible Fault Ride Through, FFRT）能力,提出采用电网故障时无功优先的改进网侧控制策略。[方法]在分析传统网侧控制策略的基础上,根据最新的故障电压穿越能力测试规程在传统网侧控制加入无功优先控制,在电网暂态故障期间优先向电网注入无功电流支撑电网电压恢复。根据改进网侧控制策略,对电网深度跌落和升高时采用卸荷电路结合改进网侧控制策略实现了风电机组的FFRT仿真运行,结合某项目6 MW半直驱风电机组,采用移动故障电压穿越测试设备进行故障电压现场测试。[结果]测试和仿真结果表明,改进网侧控制策略可提升半直驱风电系统的FFRT运行,无功电流稳定控制。[结论]改进网侧控制策略可在多种对称低电压/高电压故障工况和不对称高电压故障工况下优先向电网注入对应的稳定无功电流,有利于辅助电网电压恢复和提升半直驱风电系统的FFRT能力。     

考虑时间窗约束的海上风电机组运维方案优化

降低运维成本是保障海上风电经济效益的关键,运维方案优化对降低海上风电机组运维成本和提高发电量起着双重作用。根据风电机组零部件的可靠度模型,计算出每台风电机组最佳维修时机对应的时间窗,考虑提前维修和故障后维修的经济损失,建立包含时间窗约束的海上风电机组运维方案优化模型,然后设计基于参数优化的改进遗传算法计算出最优运维方案。最后采用某海上风电场内风电机组运维案例验证模型和算法,结果表明考虑时间窗约束的运维方案可大幅度提高海上风电的经济效益,改进遗传算法比传统遗传算法具有更强的寻优能力。     

Possible power of down‐regulated offshore wind power plants: The PossPOW algorithm

This paper proposes a method for real‐time estimation of the possible power of an offshore wind power plant when it is down‐regulated. The main purpose of the method is to provide an industrially applicable estimate of the possible (or reserve) power. The method also yields a real‐time power curve, which can be used for operation monitoring and wind farm control. Currently, there is no verified approach regarding estimation of possible power at wind farm scale. The key challenge in possible power estimation at wind farm level is to correct the reduction in wake losses, which occurs due to the down‐regulation. Therefore, firstly, the 1‐second wind speeds at the upstream turbines are estimated, since they are not affected by the reduced wake. Then they are introduced into the wake model, adjusted for the same time resolution, to correct the wake losses. To mitigate the uncertainties due to dynamic changes within the large offshore wind farms, the algorithm is updated at every turbine downstream, considering the local axial and lateral turbulence effects. The PossPOW algorithm uses only 1‐Hz turbine data as inputs and provides possible power output. The algorithm is trained and validated in Thanet and Horns Rev‐I offshore wind farms under nominal operation, where the turbines are following the optimum power curve. The results indicate that the PossPOW algorithm performs well; in the Horns Rev‐I wind farm, the strict power system requirements are met more than 70% of the time over the 24‐hour data set on which the algorithm was evaluated.