首页> 外文会议>2013 4th IEEE/PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), >Automatic mechanical fault assessment of small wind energy systems in microgrids using electric signature analysis
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Automatic mechanical fault assessment of small wind energy systems in microgrids using electric signature analysis

机译:利用电信号分析自动评估微电网中小型风能系统的机械故障

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摘要

A microgrid is a cluster of power generation, consumption and storage systems capable of operating either independently or as part of a macrogrid. The mechanical condition of the power production units, such as the small wind turbines, is considered of crucial importance especially in the case of islanded operation. In this paper, the fault assessment is achieved efficiently and consistently via electric signature analysis (ESA). In ESA the fault related frequency components are manifested as sidebands of the existing current and voltage time harmonics. The energy content between the fundamental, 5th and 7th harmonics (referred as residual value - RV) is measured and sent to the central microgrid controller. The controller compares RV to three predefined limits where inspection, maintenance and shut down of the turbine are the corresponding actions. The method is tested based on a finite element model where dynamic eccentricity and bearing outer race defect are simulated under varying fault severity and electric loading conditions
机译:微电网是发电,消耗和存储系统的集群,能够独立运行或作为宏电网的一部分运行。发电设备(例如小型风力涡轮机)的机械状况被认为至关重要,特别是在孤岛运行的情况下。在本文中,通过电子签名分析(ESA)可以高效且一致地实现故障评估。在ESA中,与故障相关的频率分量表现为现有电流和电压时间谐波的边带。测量基波,5次和7次谐波之间的能量含量(称为残余值-RV)并将其发送到中央微电网控制器。控制器将RV与三个预定义极限值进行比较,其中涡轮机的检查,维护和关闭是相应的动作。该方法基于有限元模型进行了测试,其中动态偏心率和轴承外圈缺陷在变化的故障严重程度和电负载条件下进行了模拟

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