In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area modes that are closely related to the system's inherent stability characteristics, a novel algorithm that leverages on recent advances in wide-area measurement systems (WAMSs) and ESS technologies is developed. It is shown that the proposed approach can smooth the wind power fluctuations in near real-time using a small additional ESS capacity and thus significantly enhance the monitoring of small-signal stability. Dynamic Monte Carlo simulations on the IEEE 68-bus system are used to illustrate the effectiveness of the proposed algorithm in smoothing wind power and estimating the inter-area mode statistical properties.

中文翻译：

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基于数据驱动储能系统的风电不稳定电网小信号稳定性监测算法

在本文中，我们提出了一种基于数据驱动的能量存储系统（ESS）的方法，以增强间歇风电的高渗透率的电网在线小信号稳定性监控。为了准确估计与系统固有稳定性特性密切相关的区域间模式，开发了一种新颖的算法，该算法利用了广域测量系统（WAMS）和ESS技术的最新进展。结果表明，所提出的方法可以使用少量的附加ESS容量近乎实时地消除风电波动，从而显着增强对小信号稳定性的监控。