基于改进Ibrahim时域法的电力系统振荡特性分析
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摘要
基于Ibrahim时域法的基本思想,提出一种可以识别电力系统振荡特性的改进算法,并给出了详细推导过程。所提算法可以根据故障或正常操作扰动后电力系统指定观测量的自由响应数据,识别机电模式特征值。在Matlab仿真平台上,通过对一个4机电力系统和一个8机电力系统的实例分析,证明所提方法对振荡频率和阻尼比的识别准确度比较理想,而且识别速度快、需要PMU(相量测量单元)测量点少、不遗漏模式,有较好的应用前景。
According to fundamental idea of Ibrahim Time Domain(ITD) algorithm,this paper illustrates an improved algorithm by which the small-signal stability can be assessed.Also,the course of concluding and principal formula about the improved ITD algorithm is introduced in detail.Using the real-time data sampled from free responses of selected variables in power system, which is disturbed by a fault or normal operation,the dominant eigenvalues are evaluated efficiently.In order to describe the identifying techniques,two simulation cases,one of which is a four-machine power system and the other of which is an eight-machine test system,are established in the MATLAB environment.The simulation results show that required modal information including oscillation frequency and damping is extracted successfully,and this technique also has the character of quick computation,needing fewer PMUs,without losing modes,and practical prospects.
According to fundamental idea of Ibrahim Time Domain(ITD) algorithm,this paper illustrates an improved algorithm by which the small-signal stability can be assessed.Also,the course of concluding and principal formula about the improved ITD algorithm is introduced in detail.Using the real-time data sampled from free responses of selected variables in power system, which is disturbed by a fault or normal operation,the dominant eigenvalues are evaluated efficiently.In order to describe the identifying techniques,two simulation cases,one of which is a four-machine power system and the other of which is an eight-machine test system,are established in the MATLAB environment.The simulation results show that required modal information including oscillation frequency and damping is extracted successfully,and this technique also has the character of quick computation,needing fewer PMUs,without losing modes,and practical prospects.
引文
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[7]BUJANOWSKI B J,PIERRE J W,HIETPAS S M,et al.Acom-parison of several system identification methods with application topower systems[C].Proc IEEE36th Midwest Symp Circuits Sys-tems,Detroit,MI:IEEE Press,1993,1:64-67.
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[11]徐良,江见鲸.基于样条函数的在线时域实验模态分析[J].中国矿业大学学报,2002,31(5):390-393.
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[13]KUNDUR P.Power System Stability and Control[M].NewYork:McGraw-Hill,1994.
[14]电科院计算所.电力系统分析综合程序6.2版[M].北京:中国电力科学研究院,2001.
[2]SANCHEZ-GASCAJ J,CHOWJ H.Computation of power systemlow-order models from time domain simulations using a hankel ma-trix[J].IEEE Trans on PowerSyst,1997,12(4):1461-1467.
[3]ZHOUNing.Initial results in power system identification from in-jected probing signals using a subspace method[J].IEEE Transon Power Syst,2006,21(3):1296-1302.
[4]GHASEMI H,CANIZARES C.Oscillatory stability limit predic-tion using stochastic subspace identification[J].IEEE Trans onPower Syst,2006,21(2):736-745.
[5]肖晋宇,谢小荣,胡志祥,等.电力系统低频振荡在线辨识的改进Prony算法[J].清华大学学报(自然科学版),2004,44(7):883-887.
[6]鞠平,谢欢,孟远景.基于广域测量信息在线辨识低频振荡[J].中国电机工程学报,2005,25(21):56-60.
[7]BUJANOWSKI B J,PIERRE J W,HIETPAS S M,et al.Acom-parison of several system identification methods with application topower systems[C].Proc IEEE36th Midwest Symp Circuits Sys-tems,Detroit,MI:IEEE Press,1993,1:64-67.
[8]IBRAHIMS R,MIKULCIK E C A.Method for the direct identifi-cation of vibration parameters from the free response[J].TheShock and Vibration Bulletin,1977,47(4):183-198.
[9]李中付,宋汉文,华宏星,等.一种白噪声环境激励下模态参数辨识方法[J].振动工程学报,2002,15(1):52-56.
[10]王建有,陈健云.提高阻尼识别精度的ITD两步法[J].世界地震工程,2003,19(3):35-38.
[11]徐良,江见鲸.基于样条函数的在线时域实验模态分析[J].中国矿业大学学报,2002,31(5):390-393.
[12]傅志方,华宏星.模态分析理论与应用[M].上海:上海交通大学出版社,2000.
[13]KUNDUR P.Power System Stability and Control[M].NewYork:McGraw-Hill,1994.
[14]电科院计算所.电力系统分析综合程序6.2版[M].北京:中国电力科学研究院,2001.
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