基于FSSI的环境激励下机电振荡特征参数快速识别方法研究

王丽馨

王丽馨.基于FSSI的环境激励下机电振荡特征参数快速识别方法研究[J].电测与仪表,2018,55(19):135-141.
Wang Lixin.Fast Extraction and Analysis of Electro-Mechanical Oscillations under Ambient Excitation Using FSSI Method[J].Electrical Measurement & Instrumentation,2018,55(19):135-141.

基于FSSI的环境激励下机电振荡特征参数快速识别方法研究

Fast Extraction and Analysis of Electro-Mechanical Oscillations under Ambient Excitation Using FSSI Method

DOI：

中文关键词: 环境激励随机响应低频振荡快速随机子空间辨识法 LQ分解

英文关键词:ambient excitation, random response signals, low-frequency oscillation, fast stochastic subspace identification, LQ resolution

基金项目:国家自然科学基金项目（重点项目）

作者中文名	作者英文名	单位
王丽馨	Wang Lixin	东北电力大学电气工程学院

摘要点击次数: 1401

中文摘要:

环境激励作用下的电力系统随机响应蕴含丰富的系统动态信息。随着广域测量系统的广泛应用,基于随机响应信号的低频振荡分析具有良好的应用前景。本文在对电力系统随机响应数据特征分析的基础上,提出了基于快速随机子空间辨识算法(Fast Stochastic Subspace Identification, FSSI )的电力系统机电振荡参数识别方法。FSSI算法利用LQ分解取代了传统随机子空间算法中的奇异值(SVD)分解过程,在保证SSI算法在振荡频率、阻尼比及模态振型识别精度的同时,极大地提高了分析计算的速率。IEEE 4机2区域系统和16机68节点系统仿真计算结果表明本文提出的方法具有较高的识别精度和计算速率。

英文摘要:

There is a wealth of dynamic information hidden in power system responses, which are subject to the ambient excitation. With the wide applications of wide area measurement system, analysis of low-frequency oscillations on the basis of ambient signals has a good prospect. Based on the characteristic analysis of the response data, a method for oscillation parameters identification of power system on the basis of fast stochastic subspace identification is proposed. FSSI algorithm adopts LQ resolution instead of traditional singular value decomposition process. It not only improves the rate of analysis and calculation, but also gets good recognition accuracy for oscillation frequency, damping ratio and modal shape. The high recognition accuracy and fast calculation of the proposed method is verified by the simulation results of four-machine, two-area system and 16-machine, 68-bus system.

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