基于风电场机组大部件运行状态的年度检修策略

风电场机组年度检修是保证所有风电机组正常运行的重要手段,合理的检修方案可以降低风电场运行维护成本。为确定风电场的最优年度检修方案,文章提出了一种基于大部件运行状态的风电场年度检修策略。首先,综合考虑大部件的工作役龄、维修历史及当前运行状态,以威布尔比例强度模型计算部件的故障概率;然后,定义检修改善因子,描述年度检修对部件故障概率的降低程度,建立考虑故障停机时间、故障维修费用及检修成本的年度检修策略优化模型;最后,通过算例分析验证该策略的正确性及有效性。     

风电机组维修方式的多目标决策研究

维修费用占风电场运行成本的较大比重,维修方式的选择直接影响着维修费用,科学地选择维修方式有助于降低运维成本,提高风电场的效益。文章分析了风电场风电机组结构特性及其运行、维修的特点;采用模糊层次分析法建立了风电机组维修方式的决策模型;根据比较准则,构建了三角模糊数判断矩阵;通过逐层计算权重得到备选维修方式的选择概率,并以最大概率为准则制定了维修方案。文章还以风电机组发电机维修方式的选择为例,验证了该模型的合理性和正确性。     

风电场的组合维修策略研究

为降低风电场维修成本,提出针对风电场的风电机组部件组合维修策略。在各部件故障率服从威布尔分布的基础上,确定各部件的最优预防性维修周期,进而确定各部件后续预防性维修的实施时刻。将未来一段时间内的全部维修任务按分组方案组合为多个维修组,单一维修组内包含的全部维修任务采用分层优化方法安排给多支维修队一起执行,以使在风电机组停机时间最短情况下维修队工作时间最短。对比组合维修策略与预防性维修策略的维系成本,以分组方案节约维修成本为适应度,使用遗传算法求解最优分组方案。仿真结果验证了该策略可有效减少风电机组的停机时间,降低风电场维修成本。     

基于主成分和神经网络的风力发电机主轴承故障预警

主轴承作为风力发电机组的重要部件,一旦发生故障,会影响风力发电机组整机工作的发电性能,严重时故障甚至会造成停机,不仅影响发电量,更会产生高昂的维修费用。通过运用相关性分析,根据Pearson相关系数矩阵对原有的多个指标进行分析。然后运用主成分分析,首先对数据的原始特征预处理,得到6个主成分,然后将这6个主成分作为BP神经网络的输入,运用神经网络对风力发电机的主轴承进行预警。神经网络模型结果表明,该模型对风力发电机主轴承故障预警具有非常好的识别效果,基于主成分和神经网络对风力发电机主轴承故障预警对实现机组智能故障诊断,提高机组的运行效率具有十分重要的意义。     

考虑故障相关性的风电机组维修策略

由于一般的风电机组可靠性建模忽略了各子系统间的故障相关性,必然造成可靠性评估的误差。针对这一问题,文章提出了一种考虑故障相关性的风电机组维修策略。首先,运用全概率公式和故障有向图理论,推演出子系统的综合可靠度模型,再将综合可靠度模型应用到风电机组的维修策略中。然后,建立了考虑故障相关性的风电机组状态机会维修模型和定期维修模型,状态机会维修分别采用故障后大修和小修的方法来求解状态维修阈值函数和机会维修阈值函数,定期维修以考虑降低维修费用确定定期维修周期。最后,通过实例仿真验证了考虑故障相关的风电机组维略策略在节约维修成本方面的有效性。     

数据挖掘技术在风电机组发电机轴承故障预警中的应用

随着风电装机规模的扩大和风电场投产时间的增加,风电机组的故障呈现多样化和复杂化。为提高风电场检修及故障消除的工作效率,降低运维成本,实现故障状态检修,利用风机SCADA运行数据设计,针对风机发电机轴承的故障预警算法,对发电机轴承预警,为运维人员开展故障消除与检修提供技术支撑。     

风力发电机组振动监测技术应用与实践

当前,风力发电已成为世界新能源发电中发展最迅速的行业,我国风电总装机容量已跃居世界第一。但由于缺乏关键技术,盲目扩大风电场建设,加之环境恶劣,国产风电机组故障发生率明显高于国外,这不仅增加了风力发电机组维修费用,也大大降低了发电可靠性。开展风电机组的运行状态监测,可以提前发现设备运行隐患,实现风力发电机设备的计划检修,是降低生产维修成本、防止重大事故发生的有效措施。     

可靠度约束下的不完全预防更换维修模型

针对可修系统因维修更换计划不合理而导致的不能充分利用设备剩余寿命问题,在综合考虑动态维修成本和可靠度的基础上,提出一种可靠度约束下的不完全预防更换维修方法,建立基于混合故障率的非等周期不完全预防维修模型.以可靠度为约束,给出设备更换维修周期的计算公式,采用枚举法给出最优更换阈值;以平均维修成本最小为目标,给出最佳预修次...     

一种风力发电机自动故障诊断及预测方法

为了获得故障信号精确的时域和频域信息,提出了一种Morlet小波变换补偿方法,首先计算出故障信号的时间和频率信息,然后根据Morlet小波系数中心频率峰值对计算的故障信号的幅值进行补偿,得出故障信号的准确幅值.采用Simulink模型证明该方法的可行性,并将该方法应用到测试风力发电机和实际大型风力发电机的电功率信号分析中.结果表明:该方法可以自动获得故障信号按时序排列的振幅趋势图,显示了部件发生故障后的剩余使用寿命期限;风力发电机特别是海上风力发电机的维护维修计划可根据此时间信息进行制定,降低风电运维成本.     

含多个风电场的穿透功率极限概率值计算及置信区间估计

考虑了不同地域的风速变化和负荷波动,并计及发电机组和输电线路随机故障的不同场景,采用蒙特卡罗方法进行状态抽样;构建含多个风电场的风电机组容量优化模型进行优化分析;为贴近系统未来实际运行情况,引入基于一定置信概率下风电场最大机组容量的区间值估计;IEEE30节点算例分析表明:在不同地点同时接入风电机组的效益将优于在同一地点集中接入的情况,风电场穿透功率极限区间估计更加易于适应系统未来运行状态的不确定性,从而验证了该文提出的模型和方法的可行性和正确性。     

Condition based maintenance optimization for wind power generation systems under continuous monitoring

By utilizing condition monitoring information collected from wind turbine components, condition based maintenance (CBM) strategy can be used to reduce the operation and maintenance costs of wind power generation systems. The existing CBM methods for wind power generation systems deal with wind turbine components separately, that is, maintenance decisions are made on individual components, rather than the whole system. However, a wind farm generally consists of multiple wind turbines, and each wind turbine has multiple components including main bearing, gearbox, generator, etc. There are economic dependencies among wind turbines and their components. That is, once a maintenance team is sent to the wind farm, it may be more economical to take the opportunity to maintain multiple turbines, and when a turbine is stopped for maintenance, it may be more cost-effective to simultaneously replace multiple components which show relatively high risks. In this paper, we develop an optimal CBM solution to the above-mentioned issues. The proposed maintenance policy is defined by two failure probability threshold values at the wind turbine level. Based on the condition monitoring and prognostics information, the failure probability values at the component and the turbine levels can be calculated, and the optimal CBM decisions can be made accordingly. A simulation method is developed to evaluate the cost of the CBM policy. A numerical example is provided to illustrate the proposed CBM approach. A comparative study based on commonly used constant-interval maintenance policy demonstrates the advantage of the proposed CBM approach in reducing the maintenance cost.     

Structural health and prognostics management for the enhancement of offshore wind turbine operations and maintenance strategies

Offshore wind turbines are an attractive source for clean and renewable energy for reasons including their proximity to population centers and higher capacity factors. One obstacle to the more widespread installation of offshore wind turbines in the USA, however, is that recent projections of offshore operations and maintenance costs vary from two to five times the land‐based costs. One way in which these costs could be reduced is through use of a structural health and prognostics management (SHPM) system as part of a condition‐based maintenance paradigm with smart loads management. This paper contributes to the development of such strategies by developing an initial roadmap for SHPM, with application to the blades. One of the key elements of the approach is a multiscale simulation approach developed to identify how the underlying physics of the system are affected by the presence of damage and how these changes manifest themselves in the operational response of a full turbine. A case study of a trailing edge disbond is analysed to demonstrate the multiscale sensitivity of damage approach and to show the potential life extension and increased energy capture that can be achieved using simple changes in the overall turbine control and loads management strategy. The integration of health monitoring information, economic considerations such as repair costs versus state of health, and a smart loads management methodology provides an initial roadmap for reducing operations and maintenance costs for offshore wind farms while increasing turbine availability and overall profit. Copyright © 2013 John Wiley & Sons, Ltd.     

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。     

Vibration response of a 2.3 MW wind turbine to yaw motion and shut down events

Structural health monitoring (SHM) is a process of implementing a damage detection strategy for a mechanical system. Wind turbine machinery stands to benefit from SHM significantly as the ability to detect early stages of damage before significant malfunction or structural failure occurs would reduce costs of wind power projects by reducing maintenance costs. Vibration analysis of dynamic structural response is an approach to SHM that has been successfully applied to mechanical and civil systems and shows some promise for wind turbine application. Traditionally, a setback to turbine vibration‐based SHM techniques has been the unavailability of turbine vibration response data. This study begins to address this issue by presenting vibration response for a commercial 2.3 MW turbine to a limited number of operating conditions. A database of acquired vibration response signals detailing turbine response to yaw motion, start‐up, operation and shutdown has been assembled. A Daubechies sixth‐order wavelet was used to perform an eight‐level discrete wavelet decomposition such that general trends and patterns within the signals could be identified. With further development, the presented analysis of vibration response may be integrated into routines to reduce downtime and failure frequency of utility scale wind turbines. Copyright © 2011 John Wiley & Sons, Ltd.     

海上风电场智慧运维管理系统

[目的]针对海上风电场运维安全管理,提出了海上风电场智慧运维管理系统.[方法]通过海上风电智慧调度系统、海上风电雷达多源跟踪及边界警示系统、海上风电场风机平台作业监管系统,搭建出海上风电场智慧运维管理系统.[结果]通过陆上集控中心的海上风电智慧调度系统,实现人员的安全管理以及船舶调度.通过海上风电雷达多源跟踪及边界警示...     

Availability,operation and maintenance costs of offshore wind turbines with different drive train configurations

Different configurations of gearbox, generator and power converter exist for offshore wind turbines. This paper investigated the performance of four prominent drive train configurations over a range of sites distinguished by their distance to shore. Failure rate data from onshore and offshore wind turbine populations was used where available or systematically estimated where no data was available. This was inputted along with repair resource requirements to an offshore accessibility and operation and maintenance model to calculate availability and operation and maintenance costs for a baseline wind farm consisting of 100 turbines. The results predicted that turbines with a permanent magnet generator and a fully rated power converter will have a higher availability and lower operation and maintenance costs than turbines with doubly fed induction generators. This held true for all sites in this analysis. It was also predicted that in turbines with a permanent magnet generator, the direct drive configuration has the highest availability and lowest operation and maintenance costs followed by the turbines with two‐stage and three‐stage gearboxes. Copyright © 2016 John Wiley & Sons, Ltd.     

Risk analysis of maintenance ship collisions with offshore wind turbines

A large number of offshore wind farms are planned to be built in remote deep-sea areas over the next five years. Though offshore wind sites are often located away from commercial ship traffic, the increased demand for repair or replacement services leads to high traffic densities of “maintenance ships”. To date, the risk analysis of collision between maintenance ship vessels and offshore wind turbines has received very little attention. In this paper, we propose a methodology to evaluate and prioritise the collision risks associated with various kinds of ships used for carrying out maintenance tasks on different subassemblies of wind turbines in an offshore wind farm. It is also studied how the risks of ship collision with wind turbines are distributed between two main types of maintenance tasks, namely corrective and preventative. The proposed model is tested on an offshore wind turbine with seventeen components requiring five kinds of ships to perform the maintenance tasks. Our results indicate that collision risks are mostly associated with maintenance of few components of the wind turbine and in particular, those undergoing a corrective maintenance (replacement). Finally, several mitigation strategies are introduced to minimise the risk of maintenance ship collisions with offshore wind turbines.     

Modelling wind turbine degradation and maintenance

This paper presents an asset model for offshore wind turbine reliability accounting for the degradation, inspection and maintenance processes. The model was developed based on the Petri net method that effectively captures the stochastic nature of the dynamic processes through the use of appropriate statistical distributions. The versatility of the method allows the details of the degradation and maintenance operations to be incorporated in the model. In particular, there are dependent deterioration processes between wind turbine subsystems, complex maintenance rules and the incorporation of condition monitoring systems for early failure indication to enable replacement prior to failure. The purposes of the model are to predict the future condition of wind turbine components and to investigate the effect of a specified maintenance strategy. The model outputs are statistics indicating the performance of the wind turbine components; these include the probability of being in different condition states, the expected number of maintenance actions and the average number and duration of system downtime under any maintenance strategy. Copyright © 2015 John Wiley & Sons, Ltd.     

Multi-objective opportunistic maintenance optimization of a wind farm considering limited number of maintenance groups

Several different models provided by researchers to maintain a wind turbine, but most of these models only focused on the case involved a single objective optimization problem. In practice, real cases of wind farms lead to multi-objective approach to optimize maintenance efforts. In this paper, based on an opportunistic approach, a multi-objective based model is proposed to optimize the maintenance of a farm involved several different types of wind turbines. The assumptions of stochastic behavior of wind velocity as well as the existence of a limited number for maintenance groups are also considered in this new approach. The proposed model considering imperfect maintenance, attempts (1) maximizing the expected rate of energy and (2) minimizing the total expected costs related to maintenance efforts. The opportunistic approach is also provided by the component's reliability threshold values. The comparative analysis addresses that the capability of the proposed model is more efficient compared to models addressed in literature.