摘要
实际电网中发生过多次自动发电控制(AGC)振荡,给电力系统安全稳定运行带来不利影响。为对AGC振荡进行预警、预防,利用系统正常运行时的类噪声量测数据,提出了一种AGC振荡模式辨识方法。该方法利用随机子空间法得到系统模式辨识结果,根据AGC振荡具有振荡频率低、全网频率同调振荡的特点,剔除非AGC振荡模式,并利用聚类算法得到比较可靠且辨识误差较小的AGC振荡模式。通过仿真算例和实际系统,对所提AGC振荡模式辨识算法进行验证。结果表明,所提算法能利用类噪声数据辨识出AGC振荡模式,并且具有一定的识别精度,可用于AGC振荡的风险评估。
Automatic generation control(AGC)oscillations occurred many times in real power grids,which have adverse effects on the safe and stable operation of power systems.In order to provide warning and prevention for AGC oscillations,based on the ambient measurement during the normal operation of power systems,an identification method for AGC oscillation mode is proposed.By using the stochastic subspace method,the system mode identification results are obtained.Considering that AGC oscillation has the characteristics of low oscillation frequency and homologous oscillation of the frequencies all over the grid,the modes except for AGC mode will be weed out,and the clustering algorithm is adopted to obtain the credible,low-error AGC oscillation modes.The proposed identification method of AGC oscillation mode is verified by simulation cases and a real power system.Results show that the proposed algorithm can identify the AGC mode by using the ambient data and has an acceptable identification accuracy,which can be used for the risk assessment of AGC oscillations.
作者
李凯斌
陈磊
闵勇
侯凯元
沈毅
王克非
LI Kaibin;CHEN Lei;MIN Yong;HOU Kaiyuan;SHEN Yi;WANG Kefei(Department of Electrical Engineering,Tsinghua University,Beijing 100084,China;Northeast Branch of State Grid Corporation of China,Shenyang 110180,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2022年第23期76-82,共7页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(51922061)。
关键词
自动发电控制
频率振荡
模式辨识
类噪声数据
随机子空间法
automatic generation control
frequency oscillation
mode identification
ambient data
stochastic subspace method
