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Situational awareness in an electric utility's control center of its generators' damping capabilities

机译:电力控制中心对发电机的阻尼能力的情况了解

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Poorly damped low frequency oscillations in power systems have led to system blackouts in the past. Power system stabilizers (PSSs) are installed to improve synchronous generator's oscillation damping capabilities. PSS parameter tuning by various traditional and new optimization methods are studied to ensure stable and secure operation of interconnected power systems with uncertainties. It is imperative to evaluate the tuned PSSs with the different methods to ensure continued security of a power system during operation. There is a lack of such situational awareness at electric utility control centers to assist system operators with the knowledge of synchronous generator's oscillation damping capabilities. Since the human brain responses to images and colors faster compared to text and numbers, it is desirable to develop advanced visualizations and avail them to system operators. These visualizations could utilize real-time data from phasor measurement units. This paper presents the development of a new tool for use in control centers for modal analysis visualization (MAV). Modal analysis is performed on oscillations exhibited by generators in a power system. The MAV enhances situational awareness at control centers by providing near real-time insight into generators' oscillation damping capabilities.
机译:过去,电力系统中低频振荡的衰减较弱,导致系统停电。安装了电力系统稳定器(PSS),以提高同步发电机的振荡阻尼能力。研究了通过各种传统和新型优化方法进行的PSS参数整定,以确保具有不确定性的互连电力系统的稳定和安全运行。必须使用不同的方法评估调整后的PSS,以确保电力系统在运行过程中的持续安全性。在电力公用事业控制中心缺乏这种态势感知能力,无法帮助系统操作员掌握同步发电机的振荡阻尼功能。由于人脑对图像和颜色的响应比文本和数字要快,因此需要开发高级可视化并将其提供给系统操作员。这些可视化可以利用来自相量测量单元的实时数据。本文介绍了一种新的工具的开发,该工具可用于控制中心进行模态分析可视化(MAV)。对电力系统中发电机产生的振荡进行模态分析。 MAV通过提供对发电机振荡阻尼功能的近乎实时的洞察力,增强了控制中心的态势感知能力。

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