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Analysis of low frequency oscillations in power system using EMO ESPRIT

机译:使用EMO ESPRIT分析电力系统中的低频振荡

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Identification of poorly damped low frequency oscillations present in the densely interconnected power system is of paramount importance to maintain its stable operation. Estimation of signal parameters via rotational invariance technique (ESPRIT) is a parametric method used for analysing such signals even under noisy conditions. However, this method requires precise information about the number of modes present in the signal. Hence, this work uses a combination of Exact Model Order (EMO) algorithm and ESPRIT for analysing these low frequency oscillations. The performance of the proposed method is tested using various synthetic signals with different levels of noise and PMU reporting rates. Further, the robustness of the proposed method towards noise resistance is compared with modified Prony, TLS-ESPRIT and ARMA methods. Finally, the proposed method is tested using real time probing test data obtained from Western Electricity Coordinating Council (WECC) network. Results reveal that the proposed method is accurate, precise and outperforms the other methods. (C) 2017 Elsevier Ltd. All rights reserved.
机译:识别在密集互连的电力系统中存在的阻尼不良的低频振荡对于维持其稳定运行至关重要。通过旋转不变技术(ESPRIT)估计信号参数是一种即使在嘈杂的条件下也可用于分析此类信号的参数方法。但是,此方法需要有关信号中存在的模式数量的精确信息。因此,这项工作使用精确模型顺序(EMO)算法和ESPRIT的组合来分析这些低频振荡。使用具有不同水平的噪声和PMU报告速率的各种合成信号来测试所提出方法的性能。此外,将所提出的方法对抗噪声的鲁棒性与改进的Prony,TLS-ESPRIT和ARMA方法进行了比较。最后,使用从西方电力协调委员会(WECC)网络获得的实时探测测试数据对提出的方法进行了测试。结果表明,该方法准确,准确,优于其他方法。 (C)2017 Elsevier Ltd.保留所有权利。

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