基于广域测量系统的电力系统低频振荡模态分析研究
|
摘要
近年来,随着社会经济的快速发展,互联电网的规模变得越来越大,大区电网的互联在提高电力系统运行经济性的同时使整个互联系统的动态特性变得更为复杂,用电负荷的不断增加也给电力传输带来前所未有的挑战。在此电力行业发展背景下,作为电力系统稳定与控制理论研究中热点问题之一的电力系统低频振荡就越发显得重要。电力系统低频振荡的出现会限制区域电网间的功率支援和电量交换,在严重情况下甚至会造成系统解列、大面积停电等事故。
由于电力系统低频振荡问题的重要性,因此学术界和工业界对它给予了很多的关注,出现了众多的不同方法对其进行研究分析。按照低频振荡分析数据源的不同可将低频振荡的分析方法划分为基于模型数据的分析方法和基于量测数据的分析方法等两类。第一种方法需要建立电力系统的数学模型并在确定的运行方式下进行分析,这在大电网互联的形势下由于电网复杂、运行状况不确定性增强而变得困难。实际上,发生低频振荡时电力系统的运行变量直接包含着振荡信息,因此第二种方法即利用实测数据进行分析的方法目前得到了广泛的应用。
广域测量系统(Wide Area Measurement System,WAMS)由相量测量单元(Phasor Measurement Unit, PMU)同步采集广域电网的实时运行参数,借助高速通信网络传输至数据处理中心站,得到同一时间坐标下电网全局的动态信息。电力广域频率监控网络(Wide Area Frequency Monitoring Network, FNET)是一种使用配电网电力插座作为驱动源和测量源的新型广域测量系统,具有低成本、易安装、高精度等优点,目前已经在北美电网得到广泛的部署。
在使用FNET实际测量数据对美国东部互联电网低频振荡进行模态分析时,出现了一系列影响算法分析性能与结果的问题,包括：考虑系统非线性条件下的输入信号的合适数据段选取、输入信号的采样频率选择、输入信号的时间长度设置、不同信号信噪比的多输入信号对多信号算法的影响、算法本身对于输入信号在不同信噪比条件下的参数设置等。本文即是从这些实际问题出发,进行了一系列的理论研究和创新,从而改进算法、给出算法的参数设置指导、给出算法应用指导、给出了输入信号参数设置的最优范围、采用时频分析技术选取合适数据段、多输入信号条件下的筛选方法以及由以上功能模块所组成的总体方案。仿真和实际案例分析结果表明,改进后的用于实际广域测量系统低频振荡模态分析的总体方案要明显优于现有的方法,因此本文的研究工作具有一定的理论价值和较高的实际意义。最后,基于本文提出的总体方案对2009年至2010年美国东部电网的实际低频振荡案例进行了统计分析,给出了不同分类的低频振荡出现在不同年、月份的比例和数量,对于随机选取的18个美国东部电网低频振荡实例则进行了详细的模态分析,给出了相应的振荡频率、阻尼比和模式形态分布等信息。
Recently, with the rapid development of society and economy the scale of intercon-nected power grid becomes greater and greater. The dynamic property of entire interconnec-tion has been changed to be more complicated with more interconnection of power grid which also could improve the economy for power system operation. Besides, the power load rising also brings the significant challenge of electric power transmission. Under this back-ground of electric power industry, power system low frequency oscillations which is one of the hot research topics in the area of power system stability and control becomes more and more important. Power system low frequency oscillations can limit the backup of power in different areas and exchange of electric power. What is more, in severe cases it will result in the interconnection breakup, blackout and other accidents.
Because of the importance of issue on power system low frequency oscillations, the in-dustry and academia has paid a lot of attention on it and a lot of different methods on ana-lyzing low frequency oscillations can be obtained. According to the varied data source for analyzing low frequency oscillations, methods on low frequency oscillations can be classi-fied into two types:the method based on system model and the method based on measure-ment. The first method relys on the accurate model of power system and determinate opera-tion mode which is rather difficult to acquire resulting from the complexity of power grid and uncertainty of operation mode in the case of large interconnected power grid. Actually, at the time of oscillations power system operation data contain rich oscillations information directly. Thus, the method for analyzing power system low frequency oscillations by utiliz-ing the field measurement data has been widely applied.
Wide area measurement system (WAMS) can obtain real time operation parameters of power grid from synchronized sampling by phasor measurement unit (PMU) deployed in wide geography area of power grid. Then operation parameters are transmitted to data center via the high speed communication network and the global dynamic information of entire power grid can be obtained accordingly. Wide Area Frequency Monitoring Network (FNET) is a novel WAMS by using the distribution power outlet as its power source and data source. It have characteristics of low cost, easy installation and high accuracy. Nowadays, it has been widely deployed in the North American power grid.
A lot of problems occurred when the field measurement data recorded by FNET was applied into analysis of low frequency oscillations. The problems introduced above are as follows:selection of proper data frame of input signal considering the effects of non-linearity of power system, selection of sampling frequency of input signal, time length setting of input signal, effects of varied signal-to-noise ratio (SNR) of multiple input signal on multiple signal modal analysis algorithm, presetting processing parameters of algorithms corresponding to different SNR of input signal. Based on those problems this paper obtains following significant achievements by theoretical research and innovation:improving Prony algortihm, introducing rules of presetting processing parameter of algorithms, presenting the guideline of algorithms application, acquiring the optimal range for parameter setting of in-put signal, appling time frequency technology for choosing the proper data frame of input signal, providing a filtering scheme in the case of multiple input signal with varied SNR, and a whole scheme including all the module above for analyzing the low frequency oscillations from field measurement data. The result of simulated case and practical case shows that the proposed whole scheme is obviously much better than existing methods. Therefore, the re-search of this paper has a certain theoretical value and practical significance. Finally, a sta-tistical analysis for low frequency oscillations from 2009 to 2010 occurred in American eastern interconnection is made by applying the proposed scheme. At the same time, random selected cases of eighteen are analyzed in detail and corresponding modal information in-cluding mode frequency, damping ratio and mode shape are also introduced.
由于电力系统低频振荡问题的重要性,因此学术界和工业界对它给予了很多的关注,出现了众多的不同方法对其进行研究分析。按照低频振荡分析数据源的不同可将低频振荡的分析方法划分为基于模型数据的分析方法和基于量测数据的分析方法等两类。第一种方法需要建立电力系统的数学模型并在确定的运行方式下进行分析,这在大电网互联的形势下由于电网复杂、运行状况不确定性增强而变得困难。实际上,发生低频振荡时电力系统的运行变量直接包含着振荡信息,因此第二种方法即利用实测数据进行分析的方法目前得到了广泛的应用。
广域测量系统(Wide Area Measurement System,WAMS)由相量测量单元(Phasor Measurement Unit, PMU)同步采集广域电网的实时运行参数,借助高速通信网络传输至数据处理中心站,得到同一时间坐标下电网全局的动态信息。电力广域频率监控网络(Wide Area Frequency Monitoring Network, FNET)是一种使用配电网电力插座作为驱动源和测量源的新型广域测量系统,具有低成本、易安装、高精度等优点,目前已经在北美电网得到广泛的部署。
在使用FNET实际测量数据对美国东部互联电网低频振荡进行模态分析时,出现了一系列影响算法分析性能与结果的问题,包括：考虑系统非线性条件下的输入信号的合适数据段选取、输入信号的采样频率选择、输入信号的时间长度设置、不同信号信噪比的多输入信号对多信号算法的影响、算法本身对于输入信号在不同信噪比条件下的参数设置等。本文即是从这些实际问题出发,进行了一系列的理论研究和创新,从而改进算法、给出算法的参数设置指导、给出算法应用指导、给出了输入信号参数设置的最优范围、采用时频分析技术选取合适数据段、多输入信号条件下的筛选方法以及由以上功能模块所组成的总体方案。仿真和实际案例分析结果表明,改进后的用于实际广域测量系统低频振荡模态分析的总体方案要明显优于现有的方法,因此本文的研究工作具有一定的理论价值和较高的实际意义。最后,基于本文提出的总体方案对2009年至2010年美国东部电网的实际低频振荡案例进行了统计分析,给出了不同分类的低频振荡出现在不同年、月份的比例和数量,对于随机选取的18个美国东部电网低频振荡实例则进行了详细的模态分析,给出了相应的振荡频率、阻尼比和模式形态分布等信息。
Recently, with the rapid development of society and economy the scale of intercon-nected power grid becomes greater and greater. The dynamic property of entire interconnec-tion has been changed to be more complicated with more interconnection of power grid which also could improve the economy for power system operation. Besides, the power load rising also brings the significant challenge of electric power transmission. Under this back-ground of electric power industry, power system low frequency oscillations which is one of the hot research topics in the area of power system stability and control becomes more and more important. Power system low frequency oscillations can limit the backup of power in different areas and exchange of electric power. What is more, in severe cases it will result in the interconnection breakup, blackout and other accidents.
Because of the importance of issue on power system low frequency oscillations, the in-dustry and academia has paid a lot of attention on it and a lot of different methods on ana-lyzing low frequency oscillations can be obtained. According to the varied data source for analyzing low frequency oscillations, methods on low frequency oscillations can be classi-fied into two types:the method based on system model and the method based on measure-ment. The first method relys on the accurate model of power system and determinate opera-tion mode which is rather difficult to acquire resulting from the complexity of power grid and uncertainty of operation mode in the case of large interconnected power grid. Actually, at the time of oscillations power system operation data contain rich oscillations information directly. Thus, the method for analyzing power system low frequency oscillations by utiliz-ing the field measurement data has been widely applied.
Wide area measurement system (WAMS) can obtain real time operation parameters of power grid from synchronized sampling by phasor measurement unit (PMU) deployed in wide geography area of power grid. Then operation parameters are transmitted to data center via the high speed communication network and the global dynamic information of entire power grid can be obtained accordingly. Wide Area Frequency Monitoring Network (FNET) is a novel WAMS by using the distribution power outlet as its power source and data source. It have characteristics of low cost, easy installation and high accuracy. Nowadays, it has been widely deployed in the North American power grid.
A lot of problems occurred when the field measurement data recorded by FNET was applied into analysis of low frequency oscillations. The problems introduced above are as follows:selection of proper data frame of input signal considering the effects of non-linearity of power system, selection of sampling frequency of input signal, time length setting of input signal, effects of varied signal-to-noise ratio (SNR) of multiple input signal on multiple signal modal analysis algorithm, presetting processing parameters of algorithms corresponding to different SNR of input signal. Based on those problems this paper obtains following significant achievements by theoretical research and innovation:improving Prony algortihm, introducing rules of presetting processing parameter of algorithms, presenting the guideline of algorithms application, acquiring the optimal range for parameter setting of in-put signal, appling time frequency technology for choosing the proper data frame of input signal, providing a filtering scheme in the case of multiple input signal with varied SNR, and a whole scheme including all the module above for analyzing the low frequency oscillations from field measurement data. The result of simulated case and practical case shows that the proposed whole scheme is obviously much better than existing methods. Therefore, the re-search of this paper has a certain theoretical value and practical significance. Finally, a sta-tistical analysis for low frequency oscillations from 2009 to 2010 occurred in American eastern interconnection is made by applying the proposed scheme. At the same time, random selected cases of eighteen are analyzed in detail and corresponding modal information in-cluding mode frequency, damping ratio and mode shape are also introduced.
引文
[1]G. Rogers. Power system oscillations. Holland:Kluwer Academic Publishers, 2000.
[2]Yu Y.N. Electric power system dynamics. San Diego, California:Academic Press Inc., 1983.
[3]P. Kundur. Power system stability and control. New York:McGraw-Hill Professional,1994.
[4]Anderson P M, Fouad A A. Power system control and stability(2nd Edition). USA: Wiley-IEEE Press,2002.
[5]M. Klein, G J. Rogers, and P. Kundur. A fundamental study of interarea oscillations in power systems. IEEE Trans on Power Syst.,1991,6(3):914-921.
[6]倪以信,陈寿孙,张宝霖.动态电力系统理论和分析.北京：清华大学出版社,2002.
[7]V. Sulzberger and T. Gallagher. Reliability and security:the NERC new standards development process. Power and Energy Magazine,2004,56-61.
[8]Cause of the August 14th Blackout in the United State and Canada. U.S.-Canada Power System Outage Task Force,2003.
[9]L. Pereira. Cascade to black [system blackouts]. IEEE Power and Energy Magazine, 2004,2(3):54-57.
[10]TAYLOR C W. The future in on-line security assessment and wide-area stability con-trol. Proceedings of IEEE Power Engineering Society Winter Meeting,2000:78-83.
[11]Task Force (Convener:Rehtanz C). Wide area monitoring and control for transmis-sion capability enhancement. GIGRE,2006.
[12]薛禹胜.时空协调的大停电防御框架：(二)广域信息、在线量化分析和自适应优化控制.电力系统自动化,2006,30(2)：1—10.
[13]EPRI. Assessment of applications and benefits of phasor measurement technology in power system.1997.
[14]罗建裕,王小英,鲁庭瑞,等.基于广域测量技术的电网实时动态监测系统应用.电力系统自动化,2003,27(24)：78—80.
[15]易俊,周孝信.电力系统广域保护与控制综述.电网技术,2006,30(8)：7-12.
[16]ADAMIA K M G, APOSTOLOV A P, BEGOVIC M M, et al.Wide area protection-technology and infrastructures. IEEE Trans on Power Delivery,2006,21(2): 601-609.
[17]胡志祥,谢小荣,肖晋宇,等.广域测量系统的延迟分析及其测试.电力系统自动化,2004,28(15)：39-43.
[18]A. G. Phadke. Synchronized phasor measurements in power systems. IEEE Computer Applications in Power,1993,6(2):10-15.
[19]JIANG J A, YANG J Z, LIN Y H, et al. An adaptive PMU based fault detec-tion/location technique for transmission lines. Ⅰ. Theory and algorithms. IEEE Trans on Power Delivery,2000,15 (2):486-493.
[20]JIANG J A, YANG J Z, LIN Y H, et al.. An adaptive PMU based fault detec-tion/location technique for transmission lines. Ⅱ. Theory and algorithms. IEEE Trans on Power Delivery,2000,15 (4):1136-1146.
[21]YUCS, LIU C W, YU S L, et al. A new PMU-based fault location algorithm for series compensated lines. IEEE Trans on Power Delivery,2002,17 (1):33-46.
[22]TAN J C, CROSSL EY P A, MCLAREN P G, et al. Application of a wide area backup protection expert system to prevent cascading outages. IEEE Trans on Power Delivery,2002,17 (2):375-380.
[23]SERIZAWA Y, MYOUJIN M, KITAMURAK, et al. Wide-area current differential backup protection employing broadband communications and time transfer systems. IEEE Trans on Power Delivery,1998,13(4):1046-1052.
[24]徐慧明,毕天姝,黄少锋,等.基于潮流转移因子的广域后备保护方案.电网技术,2006,30(15)：65-71.
[25]KORBA P, LARS SON M, REHTANZ C. Detection of oscillations in power systems using Kalman filtering techniques. Proceedings of IEEE Conference on Control Ap-plications,2003.183-188.
[26]KAKIMOTO N, SU GUMI Masahiro, MAKINO T, et al.Monitoring of interarea os-cillation mode by synchronized phasor measurement. IEEE Trans on Power Systems, 2006,21(1):260-268.
[27]鞠平,谢欢,孟远景,等.基于广域测量信息在线辨识低频振荡.中国电机工程学报,2005,25(22)：56-60.
[28]李大虎,曹一家.基于模糊滤波和Prony算法的低频振荡模式在线辨识方法.电力系统自动化,2007,31(1)：14-19.
[29]宋晓娜,毕天姝,吴京涛,等.基于WAMS的电网扰动识别方法.电力系统自动化, 2006,30(5)：24-28.
[30]戴晨松,薛峰,薛禹胜.受扰轨迹的分群研究.电力系统自动化,2000,24(1)：13—16.
[31]张鹏飞,薛禹胜,张启平,等.基于PMU实测摇摆曲线的暂态稳定量化分析.电力系统自动化,2004,28(20)：17-20.
[32]宋方方,毕天姝,杨奇逊.基于广域测量系统的电力系统多摆稳定性评估方法.中国电机工程学报,2006,26(16)：38-45.
[33]闵勇,丁仁杰,韩英铎,等.一次系统事故的同步相量测量结果分析.电力系统自动化,1998,22(7)：10—13.
[34]赵红嘎,薛禹胜,汪德星,等.计及PMU支路电流相量的状态估计模型.电力系统自动化,2004,28(17)：37-40.
[35]赵红嘎,薛禹胜,高翔,等.量测量的时延差对状态估计的影响及其对策.电力系统自动化,2004,28(21)：12—16.
[36]李强,周京阳,于尔铿.基于混合量测的电力系统状态估计混合算法.电力系统自动化,2005,29(19)：31—35.
[37]贺仁睦.电网动态实时监控及管理系统的构想.电力系统自动化,2002,26(5)：1—4.
[38]黄志刚,邬炜,韩英铎.基于同步相量测量的电压稳定评估算法.电力系统自动化,2002,26(2)：28-33.
[39]赵金利,余贻鑫,ZHANG Pei基于本地相量测量的电压失稳指标工作条件分析.电力系统自动化,2006,30(24)：1—4.
[40]LARSSON M, REHTANZ C.Predictive frequency stability control based on wide-area phasor measurements. Proceedingsof IEEE Power Engineering Society Summer Meeting, USA:2002.233-238.
[41]彭疆南,孙元章,王海风.基于广域量测数据和导纳参数在线辨识的受扰轨迹预测.电力系统自动化,2003,27(22)：6—11.
[42]宋方方,毕天姝,杨奇逊.基于WAMS的电力系统受扰轨迹预测.电力系统自动化,2006,30(23)：27—32.
[43]ROVNYA K S,LIU Chihwen, LU Jin, et al. Predicting future behavior of transient events rapidly enough to evaluate remedial control options in real-time. IEEE Trans on Power Systems,1995,10(3):1195-1203.
[44]KOSTEREV D N, ESZTERGAL YOS J, STIGERS C A. Feasibility study of using synchronized phasor measurements for generator dropping cont rols in the colstrip system. IEEETrans on Power Systems,1998,13 (3):755-761.
[45]STANTON S E, SLIVINSKY C, MARTIN K, et al. Application of phasor meas- urements and partial energy analysis in stabilizing large disturbances. IEEE Trans on Power Systems,1995,10(1):297-306.
[46]KAMWA I, GRONDIN R, HEBERT Y. Wide-area measurement based stabilizing control of large power systems-a decentralized/hierarchical approach. IEEE Trans on Power Systems,2001,16(1):136-153.
[47]谢小荣,肖晋宇,童陆园,等.采用广域测量信号的互联电网区间阻尼控制.电力系统自动化,2004,28(2)：37-40.
[48]江全元,白碧蓉,邹振宇.计及广域测量系统时滞影响的TCSC控制器设计.电力系统自动化,2004,28(20)：21—25.
[49]袁野,程林孙元章.采用广域测量信号的2级PSS控制策略.电力系统自动化,2006,30(24)：11—16.
[50]B. Qiu, L. Chen, V.A. Centeno, et al. Internet based Frequency Monitoring Network (FNET). in Proc. IEEE Power Engineering Society Winter Meeting.2001.1166-1171.
[51]Z. Zhong, C. Xu, B. J. Billian, et al. Power system frequency monitoring network (FNET) implementation. IEEE Trans. Power Syst.,2005,20(4):1914-1921.
[52]R. M. Gardner, Y. Liu. FNET:a quickly deployable and economic system to monitor the electric grid. in Proc. IEEE Technologies for Homeland Security Conf.2007. 209-214.
[53]Yingchen Zhang, Markham, P., Tao Xia, et al. Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications.IEEE Transactions on Smart Grid, 2010,1(2):159-167.
[54]L. Wang, J. Burgett, J. Zuo, et al. Frequency disturbance recorder design and devel-opments. in Proc. IEEE Power Engineering Society General Meeting.2007.1-7.
[55]A. J. Arana, J. N. Bank, R. M. Gardner, et al. Estimating speed of frequency distur-bance propagation through transmission and distribution systems. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2006. 1286-1290.
[56]J. N. Bank, R. M. Gardner, J. K. Wang, et al. Generator trip identification using wide-area measurements and historical data analysis. in Proc. IEEE Power Engineer-ing Society Power Systems Conference and Exposition.2006.1677-1681.
[57]R. M. Gardner, J. N. Bank, J. K. Wang, et al. Non-parametric power system event location using wide-area measurements. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2006.1668-1675.
[58]R. M. Gardner, J. K. Wang, and Y. Liu. Power system event location analysis using wide-area measurements. in Proc. IEEE Power Engineering Society General Meeting. 2007.1-7.
[59]S. S. Tsai, Z. Zhong, J. Zuo, et al. Analysis of wide-area frequency measurement of bulk power systems. in Proc. IEEE Power Engineering Society General Meeting. 2006.1-8.
[60]J. K. Wang, R. M. Gardner, and Y. Liu. Analysis of system oscillations using wide-area measurements. in Proc. IEEE Power Engineering Society General Meeting. 2006.1-6.
[61]J. N. Bank, R. M. Gardner, S. J. S. Tsai, et al. Visualization of wide-area frequency measurement information. in Proc. IEEE Power Engineering Society General Meet-ing.2007.1-8.
[62]J. Zuo, M. Baldwin, H. Zhang, et al. Use of frequency oscillations to improve event location estimation in power systems. in Proc. IEEE Power Engineering Society General Meeting.2007.1-7.
[63]J. Dong, J. Zuo, L. Wang, et al. Analysis of power system disturbances based on wide-area frequency measurements. in Proc. IEEE Power Engineering Society Gen-eral Meeting.2007.1-8.
[64]S. T. Tsai, L. Zhang, A. G. Phadke, et al. Frequency sensitivity and electromechanical propagation simulation study in large power systems. IEEE Trans. Circuits and Sys-tems I:Regular Papers,2007,54(8):1819-1828.
[65]T. Xia, H. Zhang, R. Gardner, et al. Wide-area frequency based event location esti-mation. in Proc. IEEE Power Engineering Society General Meeting.2007. 3361-3367.
[66]R. M. Gardner, W. Li, J. West, et al. Power system frequency oscillation characteris-tics. in Proc. IEEE Power Engineering Society General Meeting.2008.1-7.
[67]J. Dong, T. Xia, Y. Zhang, et al. Monitoring power system disturbances at the distri-bution level. in Proc. IEEE Power Engineering Society General Meeting.2008.1-8.
[68]W. Li, R. M. Gardner, J. Dong, et al. Wide area synchronized measurements and in-ter-area oscillation study," in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2009.1-8.
[69]T. Xia, R. Gardner, Y. Liu. FNET observations on the impact of super bowl xlii on the power grid frequency. in Proc. IEEE Power Engineering Society General Meeting. 2009.1-5.
[70]J. Dong, T. Xia, Y. Zhang, et al. Monitoring the North American interconnections at distribution level. in Proc. IEEE Power Engineering Society Power Systems Confer- ence and Exposition.2009.1-8.
[71]J. Dong, T. Xia, Y. Zhang, et al. Wide-area measurements of three North America in-terconnections at distribution level. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2009.1-8.
[72]J. Ma, J. Li, Z. Wang, et al. Wave-front arrival time analysis using wide-area fre-quency measurements. in Proc. IEEE Power Engineering Society General Meeting. 2009.1-5.
[73]Z. Yuan, T. Xia, Y. Zhang, et al.Inter-area oscillation analysis using wide area voltage angle measurements from FNET. in Proc. IEEE Power Engineering Society General Meeting.2010.1-7.
[74]MA J, DONG Z Y, ZHANG P. Comparison of BR and QR eigenvalue algorithms for power system small signal stability analysis. IEEE Trans on Power Systems,2006,21 (4):1848-1855.
[75]SANCHA J L, PEREZARRIAGA I J. Selective modal analysisof synchronizing power system oscillatory instability. IEEE Trans on Power Systems,1988,3(2): 429-438.
[76]SAUER P W, RAJAGOPALAN C, PAI M P. An explanation and generalization of the AESOPS and PEALS algorithms. IEEE Trans on Power Systems,1991,6(1): 293-299.
[77]SCOTT J A. An Arnoldi code for computing selected eigenvalue of sparse, real, un-symmetric matrices. ACM Trans on Mathematical Software,1995,21 (4):432-475.
[78]UCHIDA N, NAGAO T. A new eigen-analysis method of steady-state stability stu-dies for large power systems:S matrixme thod. IEEE Trans on Power Systems,1988, 3(2):706-714.
[79]HIROYU KI A, TERU HISA K, TOSHIO I. Nonlinear stability indexes of power swing oscillation using normal form analysis. IEEE Trans on Power Systems,2006, 21 (2):825-833.
[80]徐东杰,贺仁睦,胡国强,等.正规形方法在互联电网低频振荡分析中的应用.中国电机工程学报,2004,24(3)：18—23.
[81]JANG G, VITTAL V, KLIEMANN W. Effect of nonlinear modal interaction on con-trol performance:use of normal forms technique in control design:Part I general the-ory and procedure. IEEE Trans on Power Systems,1998,13(2):401-407.
[82]PARIZ N, SHANECHI H M, VAAHEDI E. Explaining and validating stressed power systems behavior using modal series. IEEE Trans on Power Systems.2003,18(2): 778-785.
[83]VAAHEDI E, PARIZ N, SHANECHI H M. General nonlinear modal representation of large scale power systems. IEEE Trans on Power Systems,2003,18(3): 1103-1109.
[84]吴复霞,吴浩,韩祯祥,等.电力系统非线性模式分析方法的比较.中国电机工程学报,2007,27(34)：19-25.
[85]邓集祥,刘广生,边二曼.低频振荡中的Hopf分歧研究.中国电机工程学报,1997,17(6)：391—398.
[86]AJIARAPU V, LEE B. Bifurcation theory and its application to nonlinear dynamcal phenomena in an electrical power system. IEEE Trans on Power Systems,1992, (1): 424-431.
[87]CHIANG H D, LIU C W, VARAIYA P, et al. Chaos in a simple power system. IEEE Trans on Power Systems,1993,8(4):1407-1417.
[88]BURCHETT R C, HEYDT G T. Probabilistic methods for power system dynamic stability studies. IEEE Trans on Power Apparatus and Systems,1978,97(3):695-702.
[89]WANG K W, TSE C T, TS ANG K M. Algorithm for power system dynamic stability studies taking account of the variation of load power. Electrical Power Systems Re-search,1998,46(3):221-227.
[90]王克文,钟志勇,谢志棠,等.混合使用中心矩与累加量的电力系统概率特征根分析方法.中国电机工程学报,2000,20(5)：37-41.
[91]曹一家,王春林,程时杰.电力系统静态稳定概率计算的几种新方法.电力系统自动化,1997,21(6)：13—18.
[92]易海琼,程时杰,侯云鹤,等.基于点估计的电力系统小扰动稳定概率分析.电力系统自动化,2007,31(23)：1—4.
[93]WANG K W, CHUNG C Y, TSE C T, et al. Probabilistic eigenvalue sensitivity in-dices for robust PSS site selection. IEE Proceedings:Generation,Transmission and Distribution,2001,148(6):603-609.
[94]钟志勇,王克文,谢志棠.用特征根灵敏度分析进行静态无功补偿器的设计.电力系统自动化,1999,23(14)：9—12.
[95]薛禹胜.时空协调的大停电防御框架：(二)广域信息、在线量化分析和自适应优化控制.电力系统自动化,2006,30(2)：1-10.
[96]薛禹胜,徐伟,DONG Zhaoyang,等.关于广域测量系统及广域控制保护系统的评述.电力系统自动化,2007,31(15)：1—5.
[97]张贤达.现代信号处理.北京：清华大学出版社,2002.
[98]Y. Hua, T.K. Sarkar. On SVD for estimating generalized eigenvalues of singular ma-trix pencil in noise. IEEE Transactions on Signal Processing,1991,39(4):892-900.
[99]Y. Hua, T.K. Sarkar. Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise. IEEE Transactions on Acoustics, Speech, and Signal Processing,1990,38(5):814-824.
[100]T. K. Sarkar, O. Pereira. Using the matrix pencil method to estimate the parameters of a sum of complex exponentials. IEEE Antennas and Propagation Magazine,1999, 37:48-55.
[101]M. L. Crow, A.Singh.The matrix pencil for power system modal extraction. IEEE Trans. Power Syst.,2005,20:501-501.
[102]J. M. Papy, L.D. Lathauwer, S.V. Huffel. Common pole estimation in multi-channel exponential data modelin. Signal Processing,2006,86:846-858.
[103]刘强,薛禹胜,DONG Zhaoyang,等.基于稳定域及条件概率的暂态稳定不确定性分析.电力系统自动化,2007,31(19)：1—6.
[104]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.清华大学学报(自然科学版),2004,44(7)：883-887.
[105]Trudnowski D J, Johnson J M, Hauer J F. Making Prony analysis more accurate using multiple signals. IEEE Trans on Power Systems,1999,14(1):226-231.
[106]D. J. Trudnowski, and J.E. Dagle. Effects of Generator and Static-Load Nonlineari-ties on Electromechanical Oscillations. IEEE Transactions on Power Systems, 1997,12(3):1283-1289.
[107]E. Palmer. Modal parameter estimation in the presence of nonlinearities. Australasian Universities Power Engineering Conference, Adelaide,2009.
[108]G. Ledwich, E. Palmer and A. Ghosh. Detection and estimation of nonstationary power transients. Inter-Area Oscillations in Power Systems, A Nonlinear and Nonsta-tionary Approach. A. R. Messina Editor, New York, Springer,2009.
[109]Trudnowski D.J., Johnson J.M., Hauer J.F.. SIMO system identification from meas-ured ringdowns. Proceedings of the American Control Conference,1998.
[110]N. Zhou, Z. Huang, F. Tuffner, et al. Automatic implementation of Prony analysis for electromechanical mode identification from phasor measurements. in Proc.2010 IEEE Power Engineering Society General Meeting.1-8.
[111]胡广书.现代信号处理教程.北京：清华大学出版社,2004.
[112]B. Boashash. Time-Frequency Signal Analysis-A Comprehensive Reference. Oxford: Elsevier,2003.
[113]江全元,邹振宇,曹一家,等.考虑时滞影响的电力系统稳定分析和广域控制研究进展.电力系统自动化,2005,29(3)：1-7.
[114]高宗和,戴则梅,翟明玉,等.基于统一支撑平台的EMS与WAMS集成方案.电力系统自动化,2006,30(16)：41-45.
[2]Yu Y.N. Electric power system dynamics. San Diego, California:Academic Press Inc., 1983.
[3]P. Kundur. Power system stability and control. New York:McGraw-Hill Professional,1994.
[4]Anderson P M, Fouad A A. Power system control and stability(2nd Edition). USA: Wiley-IEEE Press,2002.
[5]M. Klein, G J. Rogers, and P. Kundur. A fundamental study of interarea oscillations in power systems. IEEE Trans on Power Syst.,1991,6(3):914-921.
[6]倪以信,陈寿孙,张宝霖.动态电力系统理论和分析.北京：清华大学出版社,2002.
[7]V. Sulzberger and T. Gallagher. Reliability and security:the NERC new standards development process. Power and Energy Magazine,2004,56-61.
[8]Cause of the August 14th Blackout in the United State and Canada. U.S.-Canada Power System Outage Task Force,2003.
[9]L. Pereira. Cascade to black [system blackouts]. IEEE Power and Energy Magazine, 2004,2(3):54-57.
[10]TAYLOR C W. The future in on-line security assessment and wide-area stability con-trol. Proceedings of IEEE Power Engineering Society Winter Meeting,2000:78-83.
[11]Task Force (Convener:Rehtanz C). Wide area monitoring and control for transmis-sion capability enhancement. GIGRE,2006.
[12]薛禹胜.时空协调的大停电防御框架：(二)广域信息、在线量化分析和自适应优化控制.电力系统自动化,2006,30(2)：1—10.
[13]EPRI. Assessment of applications and benefits of phasor measurement technology in power system.1997.
[14]罗建裕,王小英,鲁庭瑞,等.基于广域测量技术的电网实时动态监测系统应用.电力系统自动化,2003,27(24)：78—80.
[15]易俊,周孝信.电力系统广域保护与控制综述.电网技术,2006,30(8)：7-12.
[16]ADAMIA K M G, APOSTOLOV A P, BEGOVIC M M, et al.Wide area protection-technology and infrastructures. IEEE Trans on Power Delivery,2006,21(2): 601-609.
[17]胡志祥,谢小荣,肖晋宇,等.广域测量系统的延迟分析及其测试.电力系统自动化,2004,28(15)：39-43.
[18]A. G. Phadke. Synchronized phasor measurements in power systems. IEEE Computer Applications in Power,1993,6(2):10-15.
[19]JIANG J A, YANG J Z, LIN Y H, et al. An adaptive PMU based fault detec-tion/location technique for transmission lines. Ⅰ. Theory and algorithms. IEEE Trans on Power Delivery,2000,15 (2):486-493.
[20]JIANG J A, YANG J Z, LIN Y H, et al.. An adaptive PMU based fault detec-tion/location technique for transmission lines. Ⅱ. Theory and algorithms. IEEE Trans on Power Delivery,2000,15 (4):1136-1146.
[21]YUCS, LIU C W, YU S L, et al. A new PMU-based fault location algorithm for series compensated lines. IEEE Trans on Power Delivery,2002,17 (1):33-46.
[22]TAN J C, CROSSL EY P A, MCLAREN P G, et al. Application of a wide area backup protection expert system to prevent cascading outages. IEEE Trans on Power Delivery,2002,17 (2):375-380.
[23]SERIZAWA Y, MYOUJIN M, KITAMURAK, et al. Wide-area current differential backup protection employing broadband communications and time transfer systems. IEEE Trans on Power Delivery,1998,13(4):1046-1052.
[24]徐慧明,毕天姝,黄少锋,等.基于潮流转移因子的广域后备保护方案.电网技术,2006,30(15)：65-71.
[25]KORBA P, LARS SON M, REHTANZ C. Detection of oscillations in power systems using Kalman filtering techniques. Proceedings of IEEE Conference on Control Ap-plications,2003.183-188.
[26]KAKIMOTO N, SU GUMI Masahiro, MAKINO T, et al.Monitoring of interarea os-cillation mode by synchronized phasor measurement. IEEE Trans on Power Systems, 2006,21(1):260-268.
[27]鞠平,谢欢,孟远景,等.基于广域测量信息在线辨识低频振荡.中国电机工程学报,2005,25(22)：56-60.
[28]李大虎,曹一家.基于模糊滤波和Prony算法的低频振荡模式在线辨识方法.电力系统自动化,2007,31(1)：14-19.
[29]宋晓娜,毕天姝,吴京涛,等.基于WAMS的电网扰动识别方法.电力系统自动化, 2006,30(5)：24-28.
[30]戴晨松,薛峰,薛禹胜.受扰轨迹的分群研究.电力系统自动化,2000,24(1)：13—16.
[31]张鹏飞,薛禹胜,张启平,等.基于PMU实测摇摆曲线的暂态稳定量化分析.电力系统自动化,2004,28(20)：17-20.
[32]宋方方,毕天姝,杨奇逊.基于广域测量系统的电力系统多摆稳定性评估方法.中国电机工程学报,2006,26(16)：38-45.
[33]闵勇,丁仁杰,韩英铎,等.一次系统事故的同步相量测量结果分析.电力系统自动化,1998,22(7)：10—13.
[34]赵红嘎,薛禹胜,汪德星,等.计及PMU支路电流相量的状态估计模型.电力系统自动化,2004,28(17)：37-40.
[35]赵红嘎,薛禹胜,高翔,等.量测量的时延差对状态估计的影响及其对策.电力系统自动化,2004,28(21)：12—16.
[36]李强,周京阳,于尔铿.基于混合量测的电力系统状态估计混合算法.电力系统自动化,2005,29(19)：31—35.
[37]贺仁睦.电网动态实时监控及管理系统的构想.电力系统自动化,2002,26(5)：1—4.
[38]黄志刚,邬炜,韩英铎.基于同步相量测量的电压稳定评估算法.电力系统自动化,2002,26(2)：28-33.
[39]赵金利,余贻鑫,ZHANG Pei基于本地相量测量的电压失稳指标工作条件分析.电力系统自动化,2006,30(24)：1—4.
[40]LARSSON M, REHTANZ C.Predictive frequency stability control based on wide-area phasor measurements. Proceedingsof IEEE Power Engineering Society Summer Meeting, USA:2002.233-238.
[41]彭疆南,孙元章,王海风.基于广域量测数据和导纳参数在线辨识的受扰轨迹预测.电力系统自动化,2003,27(22)：6—11.
[42]宋方方,毕天姝,杨奇逊.基于WAMS的电力系统受扰轨迹预测.电力系统自动化,2006,30(23)：27—32.
[43]ROVNYA K S,LIU Chihwen, LU Jin, et al. Predicting future behavior of transient events rapidly enough to evaluate remedial control options in real-time. IEEE Trans on Power Systems,1995,10(3):1195-1203.
[44]KOSTEREV D N, ESZTERGAL YOS J, STIGERS C A. Feasibility study of using synchronized phasor measurements for generator dropping cont rols in the colstrip system. IEEETrans on Power Systems,1998,13 (3):755-761.
[45]STANTON S E, SLIVINSKY C, MARTIN K, et al. Application of phasor meas- urements and partial energy analysis in stabilizing large disturbances. IEEE Trans on Power Systems,1995,10(1):297-306.
[46]KAMWA I, GRONDIN R, HEBERT Y. Wide-area measurement based stabilizing control of large power systems-a decentralized/hierarchical approach. IEEE Trans on Power Systems,2001,16(1):136-153.
[47]谢小荣,肖晋宇,童陆园,等.采用广域测量信号的互联电网区间阻尼控制.电力系统自动化,2004,28(2)：37-40.
[48]江全元,白碧蓉,邹振宇.计及广域测量系统时滞影响的TCSC控制器设计.电力系统自动化,2004,28(20)：21—25.
[49]袁野,程林孙元章.采用广域测量信号的2级PSS控制策略.电力系统自动化,2006,30(24)：11—16.
[50]B. Qiu, L. Chen, V.A. Centeno, et al. Internet based Frequency Monitoring Network (FNET). in Proc. IEEE Power Engineering Society Winter Meeting.2001.1166-1171.
[51]Z. Zhong, C. Xu, B. J. Billian, et al. Power system frequency monitoring network (FNET) implementation. IEEE Trans. Power Syst.,2005,20(4):1914-1921.
[52]R. M. Gardner, Y. Liu. FNET:a quickly deployable and economic system to monitor the electric grid. in Proc. IEEE Technologies for Homeland Security Conf.2007. 209-214.
[53]Yingchen Zhang, Markham, P., Tao Xia, et al. Wide-Area Frequency Monitoring Network (FNET) Architecture and Applications.IEEE Transactions on Smart Grid, 2010,1(2):159-167.
[54]L. Wang, J. Burgett, J. Zuo, et al. Frequency disturbance recorder design and devel-opments. in Proc. IEEE Power Engineering Society General Meeting.2007.1-7.
[55]A. J. Arana, J. N. Bank, R. M. Gardner, et al. Estimating speed of frequency distur-bance propagation through transmission and distribution systems. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2006. 1286-1290.
[56]J. N. Bank, R. M. Gardner, J. K. Wang, et al. Generator trip identification using wide-area measurements and historical data analysis. in Proc. IEEE Power Engineer-ing Society Power Systems Conference and Exposition.2006.1677-1681.
[57]R. M. Gardner, J. N. Bank, J. K. Wang, et al. Non-parametric power system event location using wide-area measurements. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2006.1668-1675.
[58]R. M. Gardner, J. K. Wang, and Y. Liu. Power system event location analysis using wide-area measurements. in Proc. IEEE Power Engineering Society General Meeting. 2007.1-7.
[59]S. S. Tsai, Z. Zhong, J. Zuo, et al. Analysis of wide-area frequency measurement of bulk power systems. in Proc. IEEE Power Engineering Society General Meeting. 2006.1-8.
[60]J. K. Wang, R. M. Gardner, and Y. Liu. Analysis of system oscillations using wide-area measurements. in Proc. IEEE Power Engineering Society General Meeting. 2006.1-6.
[61]J. N. Bank, R. M. Gardner, S. J. S. Tsai, et al. Visualization of wide-area frequency measurement information. in Proc. IEEE Power Engineering Society General Meet-ing.2007.1-8.
[62]J. Zuo, M. Baldwin, H. Zhang, et al. Use of frequency oscillations to improve event location estimation in power systems. in Proc. IEEE Power Engineering Society General Meeting.2007.1-7.
[63]J. Dong, J. Zuo, L. Wang, et al. Analysis of power system disturbances based on wide-area frequency measurements. in Proc. IEEE Power Engineering Society Gen-eral Meeting.2007.1-8.
[64]S. T. Tsai, L. Zhang, A. G. Phadke, et al. Frequency sensitivity and electromechanical propagation simulation study in large power systems. IEEE Trans. Circuits and Sys-tems I:Regular Papers,2007,54(8):1819-1828.
[65]T. Xia, H. Zhang, R. Gardner, et al. Wide-area frequency based event location esti-mation. in Proc. IEEE Power Engineering Society General Meeting.2007. 3361-3367.
[66]R. M. Gardner, W. Li, J. West, et al. Power system frequency oscillation characteris-tics. in Proc. IEEE Power Engineering Society General Meeting.2008.1-7.
[67]J. Dong, T. Xia, Y. Zhang, et al. Monitoring power system disturbances at the distri-bution level. in Proc. IEEE Power Engineering Society General Meeting.2008.1-8.
[68]W. Li, R. M. Gardner, J. Dong, et al. Wide area synchronized measurements and in-ter-area oscillation study," in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2009.1-8.
[69]T. Xia, R. Gardner, Y. Liu. FNET observations on the impact of super bowl xlii on the power grid frequency. in Proc. IEEE Power Engineering Society General Meeting. 2009.1-5.
[70]J. Dong, T. Xia, Y. Zhang, et al. Monitoring the North American interconnections at distribution level. in Proc. IEEE Power Engineering Society Power Systems Confer- ence and Exposition.2009.1-8.
[71]J. Dong, T. Xia, Y. Zhang, et al. Wide-area measurements of three North America in-terconnections at distribution level. in Proc. IEEE Power Engineering Society Power Systems Conference and Exposition.2009.1-8.
[72]J. Ma, J. Li, Z. Wang, et al. Wave-front arrival time analysis using wide-area fre-quency measurements. in Proc. IEEE Power Engineering Society General Meeting. 2009.1-5.
[73]Z. Yuan, T. Xia, Y. Zhang, et al.Inter-area oscillation analysis using wide area voltage angle measurements from FNET. in Proc. IEEE Power Engineering Society General Meeting.2010.1-7.
[74]MA J, DONG Z Y, ZHANG P. Comparison of BR and QR eigenvalue algorithms for power system small signal stability analysis. IEEE Trans on Power Systems,2006,21 (4):1848-1855.
[75]SANCHA J L, PEREZARRIAGA I J. Selective modal analysisof synchronizing power system oscillatory instability. IEEE Trans on Power Systems,1988,3(2): 429-438.
[76]SAUER P W, RAJAGOPALAN C, PAI M P. An explanation and generalization of the AESOPS and PEALS algorithms. IEEE Trans on Power Systems,1991,6(1): 293-299.
[77]SCOTT J A. An Arnoldi code for computing selected eigenvalue of sparse, real, un-symmetric matrices. ACM Trans on Mathematical Software,1995,21 (4):432-475.
[78]UCHIDA N, NAGAO T. A new eigen-analysis method of steady-state stability stu-dies for large power systems:S matrixme thod. IEEE Trans on Power Systems,1988, 3(2):706-714.
[79]HIROYU KI A, TERU HISA K, TOSHIO I. Nonlinear stability indexes of power swing oscillation using normal form analysis. IEEE Trans on Power Systems,2006, 21 (2):825-833.
[80]徐东杰,贺仁睦,胡国强,等.正规形方法在互联电网低频振荡分析中的应用.中国电机工程学报,2004,24(3)：18—23.
[81]JANG G, VITTAL V, KLIEMANN W. Effect of nonlinear modal interaction on con-trol performance:use of normal forms technique in control design:Part I general the-ory and procedure. IEEE Trans on Power Systems,1998,13(2):401-407.
[82]PARIZ N, SHANECHI H M, VAAHEDI E. Explaining and validating stressed power systems behavior using modal series. IEEE Trans on Power Systems.2003,18(2): 778-785.
[83]VAAHEDI E, PARIZ N, SHANECHI H M. General nonlinear modal representation of large scale power systems. IEEE Trans on Power Systems,2003,18(3): 1103-1109.
[84]吴复霞,吴浩,韩祯祥,等.电力系统非线性模式分析方法的比较.中国电机工程学报,2007,27(34)：19-25.
[85]邓集祥,刘广生,边二曼.低频振荡中的Hopf分歧研究.中国电机工程学报,1997,17(6)：391—398.
[86]AJIARAPU V, LEE B. Bifurcation theory and its application to nonlinear dynamcal phenomena in an electrical power system. IEEE Trans on Power Systems,1992, (1): 424-431.
[87]CHIANG H D, LIU C W, VARAIYA P, et al. Chaos in a simple power system. IEEE Trans on Power Systems,1993,8(4):1407-1417.
[88]BURCHETT R C, HEYDT G T. Probabilistic methods for power system dynamic stability studies. IEEE Trans on Power Apparatus and Systems,1978,97(3):695-702.
[89]WANG K W, TSE C T, TS ANG K M. Algorithm for power system dynamic stability studies taking account of the variation of load power. Electrical Power Systems Re-search,1998,46(3):221-227.
[90]王克文,钟志勇,谢志棠,等.混合使用中心矩与累加量的电力系统概率特征根分析方法.中国电机工程学报,2000,20(5)：37-41.
[91]曹一家,王春林,程时杰.电力系统静态稳定概率计算的几种新方法.电力系统自动化,1997,21(6)：13—18.
[92]易海琼,程时杰,侯云鹤,等.基于点估计的电力系统小扰动稳定概率分析.电力系统自动化,2007,31(23)：1—4.
[93]WANG K W, CHUNG C Y, TSE C T, et al. Probabilistic eigenvalue sensitivity in-dices for robust PSS site selection. IEE Proceedings:Generation,Transmission and Distribution,2001,148(6):603-609.
[94]钟志勇,王克文,谢志棠.用特征根灵敏度分析进行静态无功补偿器的设计.电力系统自动化,1999,23(14)：9—12.
[95]薛禹胜.时空协调的大停电防御框架：(二)广域信息、在线量化分析和自适应优化控制.电力系统自动化,2006,30(2)：1-10.
[96]薛禹胜,徐伟,DONG Zhaoyang,等.关于广域测量系统及广域控制保护系统的评述.电力系统自动化,2007,31(15)：1—5.
[97]张贤达.现代信号处理.北京：清华大学出版社,2002.
[98]Y. Hua, T.K. Sarkar. On SVD for estimating generalized eigenvalues of singular ma-trix pencil in noise. IEEE Transactions on Signal Processing,1991,39(4):892-900.
[99]Y. Hua, T.K. Sarkar. Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise. IEEE Transactions on Acoustics, Speech, and Signal Processing,1990,38(5):814-824.
[100]T. K. Sarkar, O. Pereira. Using the matrix pencil method to estimate the parameters of a sum of complex exponentials. IEEE Antennas and Propagation Magazine,1999, 37:48-55.
[101]M. L. Crow, A.Singh.The matrix pencil for power system modal extraction. IEEE Trans. Power Syst.,2005,20:501-501.
[102]J. M. Papy, L.D. Lathauwer, S.V. Huffel. Common pole estimation in multi-channel exponential data modelin. Signal Processing,2006,86:846-858.
[103]刘强,薛禹胜,DONG Zhaoyang,等.基于稳定域及条件概率的暂态稳定不确定性分析.电力系统自动化,2007,31(19)：1—6.
[104]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.清华大学学报(自然科学版),2004,44(7)：883-887.
[105]Trudnowski D J, Johnson J M, Hauer J F. Making Prony analysis more accurate using multiple signals. IEEE Trans on Power Systems,1999,14(1):226-231.
[106]D. J. Trudnowski, and J.E. Dagle. Effects of Generator and Static-Load Nonlineari-ties on Electromechanical Oscillations. IEEE Transactions on Power Systems, 1997,12(3):1283-1289.
[107]E. Palmer. Modal parameter estimation in the presence of nonlinearities. Australasian Universities Power Engineering Conference, Adelaide,2009.
[108]G. Ledwich, E. Palmer and A. Ghosh. Detection and estimation of nonstationary power transients. Inter-Area Oscillations in Power Systems, A Nonlinear and Nonsta-tionary Approach. A. R. Messina Editor, New York, Springer,2009.
[109]Trudnowski D.J., Johnson J.M., Hauer J.F.. SIMO system identification from meas-ured ringdowns. Proceedings of the American Control Conference,1998.
[110]N. Zhou, Z. Huang, F. Tuffner, et al. Automatic implementation of Prony analysis for electromechanical mode identification from phasor measurements. in Proc.2010 IEEE Power Engineering Society General Meeting.1-8.
[111]胡广书.现代信号处理教程.北京：清华大学出版社,2004.
[112]B. Boashash. Time-Frequency Signal Analysis-A Comprehensive Reference. Oxford: Elsevier,2003.
[113]江全元,邹振宇,曹一家,等.考虑时滞影响的电力系统稳定分析和广域控制研究进展.电力系统自动化,2005,29(3)：1-7.
[114]高宗和,戴则梅,翟明玉,等.基于统一支撑平台的EMS与WAMS集成方案.电力系统自动化,2006,30(16)：41-45.