基于可靠性分析的风电机组状态维修决策研究

发布时间：2018-03-04 06:18

本文选题：风电机组　切入点：状态维修　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着世界能源危机和环境的日益恶化,风电等清洁能源的发展已经成为解决全球能源问题的重要解决措施。风电行业的技术发展日趋成熟使得风电成为清洁能源电力领域中不可缺少的中坚力量。但是,随着风电机组装机容量日益增大,风电机组各个设备的故障和损坏等问题日益凸显,同时维修管理的过度和不及时威胁着机组的运行,进而造成电厂经济损失,影响电厂的经济效益,现行的定期维修体制已经不能满足现场需求,对电厂设备开展状态维修已经成为未来的发展趋势。本文以现役的风力发电机组为研究对象,开展风力发电机组状态维修决策研究,在分析设备全周期固有可靠性基础之上,分别从设备状态评价及趋势预测和状态维修时机决策角度进行分析探究,并结合故障预警和故障诊断形成完善的风电场设备状态维修决策机制,从而确保风电机组运行的安全性、可靠性和“零故障”。本文主要研究内容为： 1.全面分析风电场设备维修对象,构造维修分析决策知识库,为状态维修决策提供知识支持。从风电机组的结构、重要功能部件、可靠性分析和监测的角度全面剖析状态维修决策的研究对象,针对风电机组不同设备基础知识分析,选择不同维修决策模型,为接下来的维修决策过程提供基本的信息支持。 2.建立风力发电机组基于实时可靠性分析的状态维修决策模型,结合风电机组在线监测数据,实时的评价机组以及设备的实时可靠性,了解风电设备当前所处状态,对设备所处状态进行划分。通过建立实时可靠性趋势预测模型判断风电设备状态的发展趋势及状态变化的速度,并根据预先设置的状态阈值,给出运行和维修建议。 3.建立基于比例失效模型的状态维修决策,结合现有风电场故障预警、诊断技术的发展,提出了一套完整的状态维修决策体系,通过MATLAB编程实现该模型的参数估计,利用最大可用度确定最优维修阂值,并绘制其维修决策图,通过实际风电机组状态监测数据在维修决策图中描点,得到最优的维修时机决策曲线,最终确定需要实施的维修活动。
[Abstract]:With the world energy crisis and the worsening of the environment, The development of clean energy, such as wind power, has become an important solution to the global energy problem. With the development of wind power technology, wind power has become an indispensable backbone of clean energy and power. With the increasing installed capacity of wind turbine, the problems such as failure and damage of each equipment of wind turbine are becoming more and more prominent. At the same time, the excessive maintenance management threatens the operation of the unit and causes the economic loss of power plant. Affecting the economic benefits of power plants, the current periodic maintenance system can no longer meet the demand on the spot, and it has become a trend of development in the future to carry out condition maintenance for power plant equipment. This paper takes the active wind turbine as the research object, carries out the wind turbine condition maintenance decision research, on the basis of analyzing the inherent reliability of the whole period of the equipment, From the point of view of equipment status evaluation, trend prediction and condition maintenance timing decision, and combining with fault warning and fault diagnosis to form a perfect decision-making mechanism of wind farm equipment condition maintenance. So as to ensure the safety, reliability and "zero failure" of wind turbine. The main contents of this paper are as follows:. 1. Analyzing the maintenance object of wind farm equipment, constructing the knowledge base of maintenance analysis decision, providing knowledge support for condition maintenance decision. From the perspective of reliability analysis and monitoring, the research object of condition maintenance decision making is analyzed. According to the basic knowledge analysis of different equipments of wind turbine, different maintenance decision models are selected to provide basic information support for the next maintenance decision-making process. 2. Establish the condition maintenance decision model of wind turbine based on real-time reliability analysis, combine the on-line monitoring data of wind turbine, evaluate the real-time reliability of wind turbine and equipment in real time, understand the current status of wind power equipment. The state of the equipment is divided, and the development trend and the speed of the state change of the wind power equipment are judged by establishing the real-time reliability trend prediction model, and the operation and maintenance suggestions are given according to the preset state threshold. 3. The decision of condition maintenance based on proportional failure model is established. Combined with the development of existing wind farm fault warning and diagnosis technology, a complete decision system of condition maintenance is put forward. The parameter estimation of the model is realized by MATLAB programming. The optimal maintenance threshold value is determined by the maximum availability, and the maintenance decision diagram is drawn, and the optimal maintenance opportunity decision curve is obtained by drawing the points in the maintenance decision diagram of the actual wind turbine condition monitoring data. Finalize maintenance activities to be implemented.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM315

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