Low-frequency oscillation (LFO) is among the key factors that threaten interconnected power grids’ security and stability and restrict transfer capability. In particular, power systems incur now and then weak damping and forced oscillations. To monitor and control LFO, the principles of online calculation and analysis of two types of LFO are studied in this paper. The big data of wide area measurements is an important information source of LFO analysis. Hence, we should make sure it has access to online system continuously, accurately, and reliably. Nevertheless, the conventional linear data store model has difficulty to meet the processing requirements of high rate, multiple concurrency, and high reliability. To deal with it, a new model of double-set elastic store is proposed in this paper. It transforms the storage space linear model to plane model, realizes the management of power system substation group sets in vertical direction and the management of multiple Phase Measurement Units (PMU) uploading data sets in horizontal direction, and hence solves the problems in continuous and reliable access of the wide area measurements data, which is dense and of large scale and has quick update rate, providing technical support of accuracy and robustness of LFO analysis. The performance test and practical application of the proposed new model of double-set elastic store validate its accuracy.

中文翻译：

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低频振荡分析中的WAMS大数据弹性存储模型研究

低频振荡（LFO）是威胁互连电网的安全性和稳定性并限制传输能力的关键因素之一。尤其是电力系统会时而产生弱阻尼和强制振荡。为了监视和控制LFO，本文研究了两种LFO的在线计算和分析原理。广域测量的大数据是LFO分析的重要信息来源。因此，我们应该确保它能够连续，准确和可靠地访问在线系统。然而，传统的线性数据存储模型难以满足高速率，多并发和高可靠性的处理要求。针对这种情况，本文提出了一种新的双设定弹性存储模型。将存储空间线性模型转换为平面模型，实现了电力系统变电站组的纵向管理，并实现了多个相测量单元（PMU）在水平方向上载数据的管理，从而解决了连续可靠的问题。可以访问密集，大规模且更新速度快的广域测量数据，为LFO分析的准确性和鲁棒性提供了技术支持。所提出的新型双组弹性存储模型的性能测试和实际应用证明了其准确性。从而解决了密集，规模大，更新速度快的广域测量数据连续可靠访问的问题，为LFO分析的准确性和鲁棒性提供了技术支持。所提出的新型双组弹性存储模型的性能测试和实际应用证明了其准确性。从而解决了密集，规模大，更新速度快的广域测量数据连续可靠访问的问题，为LFO分析的准确性和鲁棒性提供了技术支持。所提出的双组弹性存储新模型的性能测试和实际应用证明了其准确性。