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LowFrequency Oscillation Mode Source Identification with Wide-Area Measurement System

机译:广域测量系统识别低频振荡模式源

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It can avoid low frequency oscillation in power grid if we can detect the oscillation mode with low damping ratio and identify the source in early stage. This paper presents the Frequency Domain Decomposition (FDD) method, which can extract the low frequency oscillation modes from measurements of Phasor Measurement Units (PMU) in normal operation condition. The damping ratio, modal frequency and the mode shape of poorly damped oscillatory modes can be directly determined from ambient PMU measurements. After the oscillation modes are identified by FCC method, the next step is to identify the source of oscillation modes and the Pearson correlation coefficient (PCC) method is proposed. Combined with FDD and PCC from status data in energy management system (EMS) and the oscillation mode results, we can identify the source of oscillation mode with high correlations. The case study shows that the combination of FDD and PCC is a very efficient way to process large volume of WAMS data and EMS data, identifying low frequency oscillation mode source, and provide possible way to take early actions preventing low frequency oscillation in power system.
机译:如果我们能够检测出低阻尼比的振荡模式并在早期识别出源,就可以避免电网中的低频振荡。本文提出了频域分解(FDD)方法,该方法可以从正常工作条件下的相量测量单元(PMU)的测量中提取低频振荡模式。阻尼比,模态频率和阻尼较弱的振荡模式的模式形状可以直接从环境PMU测量中确定。在通过FCC方法确定了振动模式之后,下一步是确定振动模式的来源,并提出了Pearson相关系数(PCC)方法。结合能量管理系统(EMS)中状态数据中的FDD和PCC以及振荡模式的结果,我们可以识别出具有高度相关性的振荡模式的来源。案例研究表明,FDD和PCC的组合是处理大量WAMS数据和EMS数据,识别低频振荡模式源的非常有效的方法,并为采取早期行动防止电力系统中的低频振荡提供了可能的方法。

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