Online oscillatory stability estimation of power system using DSI Toolbox

Prossy Mutesi, W. Wangdee, Sompol Chumnanvanichkul
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引用次数: 1

Abstract

Electric power systems around the world are experiencing increased power transfer over the long interconnected transmission systems, and hence they become increasingly stressed in terms of oscillatory stability as the system damping capabilities have reduced. This paper investigates the potential utilization of the dynamic system identification (DSI) Toolbox, the open source software, for an online oscillatory stability monitoring purposes. Actual measured data based on two oscillation events occurred in Thailand power grid have been used to validate the correctness and effectiveness of the oscillatory frequency mode estimation. Different sliding window lengths to process the measured data along the time window to continuously estimate the oscillatory mode parameters were investigated, and the reasonable window length was then recommended. In addition, the study verified the effectiveness of the damping ratio estimates obtained from the DSI Toolbox and compared against those estimates obtained using the commercial software tool. The results indicates that the DSI Toolbox offers fairly accurate estimation of the oscillation mode information for both ambient noise and forced oscillation periods, and thus its algorithms could be adopted for online oscillatory stability monitoring tool to enhance the system operational capability.
基于DSI工具箱的电力系统振荡稳定性在线估计
世界各地的电力系统都在经历长时间互联传输系统的电力传输增加,因此随着系统阻尼能力的降低,它们在振荡稳定性方面变得越来越紧张。本文研究了动态系统识别(DSI)工具箱的潜在利用,这是一种开源软件,用于在线振荡稳定性监测。利用泰国电网两次振荡事件的实测数据,验证了振荡频率模态估计的正确性和有效性。研究了沿时间窗处理实测数据以连续估计振荡模态参数的不同滑动窗长度,并推荐了合理的滑动窗长度。此外,该研究验证了从DSI工具箱获得的阻尼比估计的有效性,并与使用商业软件工具获得的估计进行了比较。结果表明,DSI工具箱能较准确地估计环境噪声和强迫振荡周期下的振荡模态信息,其算法可用于在线振荡稳定性监测工具,以提高系统的运行能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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