基于WAMS的电力系统状态估计及轨迹稳定信息提取研究
|
摘要
广域同步测量系统(WAMS)依次实现了电力系统的静态状态断面,故障(扰动)突变场景,以及后续的暂(动)态摇摆三个阶段的全过程同步电气量测,其实测数据蕴含了从静态到动态的丰富信息,对电力系统运行与稳定控制具有重要的意义;然而,如何把有用信息从海量的WAMS原始实测数据中提取出来,仍是一个棘手的难题。因此本论文针对WAMS实测数据,分别进行了静态断面、动态轨迹、扰动场景和暂态稳定的数据挖掘和信息提取研究,主要工作如下:
提出了一种同时计及相量测量单元(PMU)节点电压和支路电流相量的混合量测非线性静态状态估计方法。该方法充分保留各种量测自身的精度,直接利用PMU支路电流相量量测(经过必要的坐标变换),与PMU节点电压相量量测,以及原SCADA传统量测一起进行混合非线性迭代计算。对本方法的量测误差也进行了详细的分析,并与其它方法的量测转换误差进行了比较。仿真结果表明,该方法与其它混合量测状态估计相比,在估计精度上有较明显改善,在收敛次数和滤波效果上也有所改进。为减少提出方法的收敛时间,还进一步实现了它的快速解耦算法。
针对WAMS动态轨迹存在量测误差的问题,提出了一种电力系统机电暂态过程中的分布式状态估计方法。该方法选定发电机转子功角和电角速度作为待估计的状态量,利用PMU实测的发电机输出电磁功率实现了对发电机转子运动方程和外部网络的解耦,提出了基于线性卡尔曼滤波方法的动态估计模型;并对WAMS的量测误差以及模型动态噪声进行了详细的分析;给出了算法的整体流程及相应的坏数据检测和剔除方法。仿真结果表明,所提方法具有理想的估计精度,且计算速度快,能够满足实时应用的要求,可以更好地服务于电力系统安全稳定监控系统。
提出了一种基于WAMS的电力系统扰动识别方法。该方法一方面选取扰动后的PMU实测正序支路电流相量作为特征提取量,另一方面利用叠加原理,在扰动分量网络中求取支路电流的估计扰动分量,进而通过实测特征提取量和预设事件的估计扰动分量之间的快速匹配(利用距离二范数),实现了对扰动类型和位置的快速有效识别,以改进稳控系统的故障场景识别和匹配。仿真结果表明了该方法的有效性。
探讨了对WAMS实时动态轨迹应用轨迹量化分析工具时所遇到的一些难题,提出了一种基于WAMS的电力系统暂态稳定信息提取工程化方法。针对稳定裕度的求取,分析比较了基于辨识的参数冻结法和曲线外推法;在选取合适观察断面的同时,提出了一种通过构造综合功角来进行分群的新方法;还提出了一种综合判据以判别当轨迹遇到动态鞍点(DSP)点时是否会真正失稳。仿真结果验证了该工程化方法的有效性,该方法可以在系统的失稳特征尚不明显时,就及时判别出系统的稳定性。
Wide Area Measurement System (WAMS) realize the measurements for the complete dynamic process of power systems in three different time frames which includes steady snapshot, fault (perturbation) scenarios and electromechanical swing. The WAMS measurements implicate power system information from steady state to dynamic state. It is still a hard task that how to extract the useful information from the raw WAMS data. The dissertation focuses on data mining and information extraction for power system steady state, fault scenario and transient stability, after eliminating the noise and bad data of raw WAMS data. They are mainly including:
Firstly, a novel hybrid nonlinear state estimator including PMU node voltage phasor and branch current phasor measurements is proposed. The proposed estimator adopts the PMU current phasor measurements directly (after necessary coordinates transform), and incorporates them with PMU voltage phasor measurements and conventional SCADA data to solve the nonlinear equations iteratively. The error covariance of indirect measurements caused by coordinates transformation is analyzed in detail, and is compared with those caused by SCADA measurements transformation. The simulation results demonstrate that the proposed estimator has higher estimation precision, better convergence capability and less iteration numbers. To further reduce the convergence time, the fast decoupled algorithm of the proposed method is realized as well.
Aiming at the measurement errors of WAMS dynamic data, a distributed dynamic state estimator based on WAMS during power system electromechanical transient process is proposed. The proposed estimator chooses the rotor angle and electrical angular velocity as the generator variables to estimate. The generator output power measured by PMU is used to decouple the generator rotor movement equation and the outer network equation. And the linear Kalman filter based dynamic state estimator mathematical model is presented. The WAMS measurement noise and dynamic model noise are analyzed in detail. The total flow chart and the bad data detection and elimination approach are given as well. The simulation results indicate that the proposed dynamic estimator has high estimation precision and fast computational speed; therefore, which can satisfy the real-time requirements of the dynamic monitoring and control system.
For the information extraction for fault scenarios, the measured positive sequence phasors of branch currents is adopted as characteristic variables, and a novel disturbance recognition algorithm based on WAMS is proposed. Utilizing the principle of superposition, the proposed method injects the relative currents into the presupposed event node to get the estimated disturbance components of the branch currents in the disturbance network. The PMU measured vector consists of PMU measured positive sequence phasors of branch currents, and the presupposed event vector consists of estimated disturbance components of the branch current phasors for each presupposed event. Then, the 2-norm of the distance vector between the measured vector and each presupposed event vector is calculated and the minimal 2-norm indicates the true event. The simulation results show that the proposed disturbance recognition algorithm can recognize and match the fault (disturbance) scenarios correctly and rapidly, which is useful for the remedial control system.
Aiming at the transient stability information extract for estimated WAMS trajectories, the dissertation discuss some problems in the application of EEAC (extended equal area criterion). After simulation and analysis, it is pointed out that the frozen parameter method using admittance online identifying technology is not a proper way to calculate the stability margin in large systems with measurement noise, and the curve extrapolation technology should be a better alternative. A novel integrated rotor angle criterion is proposed to identify the true critical cluster when observed snapshot time is chosen properly. And an integrated criterion is proposed to judge whether the DSP is the true DSP which resulted in losing stability. Finally, the flowchart of transient stability information extraction based on WAMS is proposed, and the simulation results demonstrate that the proposed method is effective. It can judge transient instability even if the characteristic of instability is not obvious.
提出了一种同时计及相量测量单元(PMU)节点电压和支路电流相量的混合量测非线性静态状态估计方法。该方法充分保留各种量测自身的精度,直接利用PMU支路电流相量量测(经过必要的坐标变换),与PMU节点电压相量量测,以及原SCADA传统量测一起进行混合非线性迭代计算。对本方法的量测误差也进行了详细的分析,并与其它方法的量测转换误差进行了比较。仿真结果表明,该方法与其它混合量测状态估计相比,在估计精度上有较明显改善,在收敛次数和滤波效果上也有所改进。为减少提出方法的收敛时间,还进一步实现了它的快速解耦算法。
针对WAMS动态轨迹存在量测误差的问题,提出了一种电力系统机电暂态过程中的分布式状态估计方法。该方法选定发电机转子功角和电角速度作为待估计的状态量,利用PMU实测的发电机输出电磁功率实现了对发电机转子运动方程和外部网络的解耦,提出了基于线性卡尔曼滤波方法的动态估计模型;并对WAMS的量测误差以及模型动态噪声进行了详细的分析;给出了算法的整体流程及相应的坏数据检测和剔除方法。仿真结果表明,所提方法具有理想的估计精度,且计算速度快,能够满足实时应用的要求,可以更好地服务于电力系统安全稳定监控系统。
提出了一种基于WAMS的电力系统扰动识别方法。该方法一方面选取扰动后的PMU实测正序支路电流相量作为特征提取量,另一方面利用叠加原理,在扰动分量网络中求取支路电流的估计扰动分量,进而通过实测特征提取量和预设事件的估计扰动分量之间的快速匹配(利用距离二范数),实现了对扰动类型和位置的快速有效识别,以改进稳控系统的故障场景识别和匹配。仿真结果表明了该方法的有效性。
探讨了对WAMS实时动态轨迹应用轨迹量化分析工具时所遇到的一些难题,提出了一种基于WAMS的电力系统暂态稳定信息提取工程化方法。针对稳定裕度的求取,分析比较了基于辨识的参数冻结法和曲线外推法;在选取合适观察断面的同时,提出了一种通过构造综合功角来进行分群的新方法;还提出了一种综合判据以判别当轨迹遇到动态鞍点(DSP)点时是否会真正失稳。仿真结果验证了该工程化方法的有效性,该方法可以在系统的失稳特征尚不明显时,就及时判别出系统的稳定性。
Wide Area Measurement System (WAMS) realize the measurements for the complete dynamic process of power systems in three different time frames which includes steady snapshot, fault (perturbation) scenarios and electromechanical swing. The WAMS measurements implicate power system information from steady state to dynamic state. It is still a hard task that how to extract the useful information from the raw WAMS data. The dissertation focuses on data mining and information extraction for power system steady state, fault scenario and transient stability, after eliminating the noise and bad data of raw WAMS data. They are mainly including:
Firstly, a novel hybrid nonlinear state estimator including PMU node voltage phasor and branch current phasor measurements is proposed. The proposed estimator adopts the PMU current phasor measurements directly (after necessary coordinates transform), and incorporates them with PMU voltage phasor measurements and conventional SCADA data to solve the nonlinear equations iteratively. The error covariance of indirect measurements caused by coordinates transformation is analyzed in detail, and is compared with those caused by SCADA measurements transformation. The simulation results demonstrate that the proposed estimator has higher estimation precision, better convergence capability and less iteration numbers. To further reduce the convergence time, the fast decoupled algorithm of the proposed method is realized as well.
Aiming at the measurement errors of WAMS dynamic data, a distributed dynamic state estimator based on WAMS during power system electromechanical transient process is proposed. The proposed estimator chooses the rotor angle and electrical angular velocity as the generator variables to estimate. The generator output power measured by PMU is used to decouple the generator rotor movement equation and the outer network equation. And the linear Kalman filter based dynamic state estimator mathematical model is presented. The WAMS measurement noise and dynamic model noise are analyzed in detail. The total flow chart and the bad data detection and elimination approach are given as well. The simulation results indicate that the proposed dynamic estimator has high estimation precision and fast computational speed; therefore, which can satisfy the real-time requirements of the dynamic monitoring and control system.
For the information extraction for fault scenarios, the measured positive sequence phasors of branch currents is adopted as characteristic variables, and a novel disturbance recognition algorithm based on WAMS is proposed. Utilizing the principle of superposition, the proposed method injects the relative currents into the presupposed event node to get the estimated disturbance components of the branch currents in the disturbance network. The PMU measured vector consists of PMU measured positive sequence phasors of branch currents, and the presupposed event vector consists of estimated disturbance components of the branch current phasors for each presupposed event. Then, the 2-norm of the distance vector between the measured vector and each presupposed event vector is calculated and the minimal 2-norm indicates the true event. The simulation results show that the proposed disturbance recognition algorithm can recognize and match the fault (disturbance) scenarios correctly and rapidly, which is useful for the remedial control system.
Aiming at the transient stability information extract for estimated WAMS trajectories, the dissertation discuss some problems in the application of EEAC (extended equal area criterion). After simulation and analysis, it is pointed out that the frozen parameter method using admittance online identifying technology is not a proper way to calculate the stability margin in large systems with measurement noise, and the curve extrapolation technology should be a better alternative. A novel integrated rotor angle criterion is proposed to identify the true critical cluster when observed snapshot time is chosen properly. And an integrated criterion is proposed to judge whether the DSP is the true DSP which resulted in losing stability. Finally, the flowchart of transient stability information extraction based on WAMS is proposed, and the simulation results demonstrate that the proposed method is effective. It can judge transient instability even if the characteristic of instability is not obvious.
引文
[1] B.A. Carreras, D.E. Newman, I. Dobson, A.B. Poole, Evidence for self organized criticality in electric power system blackouts, IEEE Transactions on Circuits and Systems, part I, 2004,51(9): 1733-1740
[2] D. Kosterev, S. Yirga, and V. Venkatasubramanian, Validation report of the August 10, 1996 WSCC disturbance, Operating Capability Study Group, Western Systems Coordinating Council, March 1997
[3]王梅义.有感于美国西部电网大停电.电网技术,1996,20(9):43~46
[4] Taylor C W, Erickson D C. Recording and Analyzing the July 2 cascading Outage, IEEE Computer Applications in Power, 1997, 10(1): 26~30.
[5]陈建业,王仲鸣.1996年夏季美国西部电力系统停电事故.国际电力,1998,3(2):52~56
[6]何大愚.对于美国西部电力系统的1996年7月2日大停电事故的初步认识.电网技术,1996,20(9):35~39
[7] R. Aggarwal, R. Daschmans, R. Schellberg, V. Venkatasubramanian, and S. Yirga, Validation studies of the July 2, 1996 WSCC system disturbance event, Operating Capability Study Group, Western Systems Coordinating Council, July 1997
[8] Kosterev D N, Taylor C W, Mittestadt W A, Model validation for the August 10, 1996 WSCC outage, IEEE Trans. on Power Systems, 1999, 14(3): 967~979
[9]卢卫星,舒印丝,史连军.美国西部电力系统1996年8月10日大停电事故.电网技术,1996,20(9):40~42
[10]甘德强,胡江溢,韩祯祥.2003年国际若干停电事故思考.电力系统自动化,2004,28(3):1~4.
[11] U.S.-Canada power systems outage task force final report on the august 14, 2003 blackout in the United States and Canada[R/OL]. http: //www.ferc.gov/, April, 2004
[12]薛禹胜.综合防御由偶然故障演化为电力灾难——北美“8·14”大停电的警示.电力系统自动化,2003,27(18):1~5
[13]印永华,郭剑波,赵建军,等.美加“8.14”大停电事故初步分析以及应吸取的教训[J].电网技术,2003,27(10):8~11
[14]何大愚.一年以后对美加“8.14”大停电事故的反思.电网技术,2004,28(21):1～5
[15]王伟.“8.14”美加大停电突显EMS实用化的正确性.华北电力技术,2004,7:35~36
[16]谢旭.从“8.14”美加大停电看电网调度自动化面临的挑战.华北电力技术,2004,7:37~41
[17]蔡敏,孙光辉,吴晓辰,等.稳定控制所用交流设备跳闸判据的分析及应用[J].电力系统自动化,2007,31(8):46~51.
[18] A. G. Phadke,“Synchronized Phasor Measurements in Power Systems”,IEEE Computer Applications in Power, 1993, 6(2),:10~15
[19] Burnett R O, Phadke A G, et al.Synchronized Phasor Measurements of a Power System Event. IEEE Trans on PS,1994(3):1643~1650
[20] Martin K E, Benmouyal G, Adamiak M G, et al. IEEE Standard for Synchrophasors for Power Systems. IEEE Transactions on Power Delivery, 1998, 13(1): 73– 77
[21] F.J.Marin, F.G.Lagos, G.Joya. Genetic Algorithms for Optimal Placement of Phasor Measurement Units in Electrical Networks. Electronics Letters, 39(19), Sept.2003
[22] B.Milosevic, M.Begovic. Nondominated Sorting Genetic Algorithm for Optimal Phasor Measurement Placement IEEE Trans. On Power Systems,18(1), Feb,2003:69~75
[23] R.F.Nuqui, A.G.Phadke. Phasor Measurement Unit Placement Based on Incomplete Observability IEEE Power Engineering Society Summer Meeting, 21~25 July 2002:2888~893
[24] A G Phadke. Synchronized Phasor Measurements - A Historical Overview. IEEE/PES Transmission and Distribution Conference and Exhibition: Asia Pacific, 2002, Vol.1: 476~479
[25] Bhargava B. Synchronized Phasor Measurement System project at Southern California Edison Co. IEEE Power Engineering Society Summer Meeting, July 1999, Vol.1:16– 22
[26]国家电网公司.国家电网公司“十一·五”科技发展规划.国家电网公司,2006.2
[27] L.Mili, T.Baldwin, R.Adapa. Phasor Measurement Placement for Voltage Stability Analysis of Power Systems. Proceeding of 29th Conference on Decision and Control. Honolulu,Hawaii.December 1990
[28] Phadke A G, Pickett B, Adamiak M, et a1. Synchronized Sampling and Phasor Measurements for Relaying and Control.IEEE Trans. on Power Delivery, 1994, 9(1) 442~452
[29]蔡运清,汪磊,Kip Morison,Prabha Kundur,周逢权,郭志忠.广域保护(稳控)技术的现状及展望.电网技术,2004,28(8):20～25
[30]中国电力科学研究院系统研究所.跨区电网动态稳定监控系统可行性研究.北京:中国电力科学研究院,2004.10
[31]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.2003,27(24):78～80
[32]许树楷,谢小荣,辛耀中.基于同步向量测量技术的广域测量系统应用现状及发展前景.电网技术,2005,29(2):44～49
[33]谢小荣,李红军,吴京涛,张涛,童陆园.同步相量技术应用于电力系统暂态稳定性控制的可行性分析.电网技术,2004,28(1):10～14
[34]薛禹胜,徐伟,Zhaoyang Dong.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
[35]常乃超,郭志忠.基于广域量测的全局非线性励磁控制.中国电机工程学报,2004,24(2):43~48
[36]张保会,谢欢,于广亮等.基于广域轨迹信息的多机系统暂态不稳定性快速预测方法.电网技术,2006,30(19):53~58
[37]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(2):38~45
[38]何飞跃,段献忠.基于广域测量的滑模TCSC控制器设计.电网技术,2006,30(23):50~55
[39]韩英铎,严剑峰,谢小荣.电力系统机电暂态过程主导动态参数的在线辨识.中国电机工程学报,2006,26(2):1~6
[40]丁军策,蔡泽祥,王克英.基于广域测量系统的状态估计研究综述.电力系统自动化,2006,30(7):98-103
[41] Phadke A G, Thorp J S, Karimi K J,et al. State Estimation with Phasor Measurements. IEEE Trans on Power Systems, 1986,1,(1):233~241
[42] Baldwin T L,Mili L Boison,M B etal. Power System Observability with Minimal Phasor Measurement Placement. IEEE Trans on Power Systems, 1993,8,(2):707~715
[43]卢志刚,许世范,史增洪,等.部分电压和电流相量可测量时电压相量的状态估计.电力系统自动化,2000,24(1):42~44
[44] W.M. Lin, J.H. Teng. State Estimation for Distribution Systems with Zero-injection Constraints, IEEE Transactions on Power Systems, 1996,11(1): 518~524
[45]程浩忠,袁青山,汪一华,等.基于等效电流量测变换的电力系统状态估计方法.电力系统自动化,2000,24(14):25~29
[46]丁军策,蔡泽祥,王克英.相量测量单元测量值对状态估计中等效电流量变换算法的影响.电网技术,2005,29(5):47~51
[47]丁军策,蔡泽祥,王克英.极坐标系下的快速等效电流量测变换状态估计方法.电力系统自动化,2005,29(5):31~33
[48]丁军策,蔡泽祥,王克英.基于广域测量系统的混合量测状态估计方法.中国电机工程学报,2006,26(2):58~63
[49]李强,周京阳,于尔铿,等.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
[50]李强,周京阳,于尔铿,等.基于相量量测的电力系统线性状态估计.电力系统自动化,2005,29(18):24~28
[51] Ming Zhou, Virgilio A. Centeno, James S. Thorp, et al. An Alternative for Including Phasor Measurements in State Estimators. IEEE Transactions on Power Systems, 2006,21(4): 1930~1937
[52] Thorp J S, Phadke A G, Karimi K J,et al. Real Time Voltage-phasor Measurements for Static State Estimation. IEEE Trans on Power System, 1986,1,(1):233~241
[53] Zivanovic R, Carnis C. Implementation of PMU Technology in Static State Estimation: an Overview. In Proceedings of 1996 IEEE AFRICON,4th AFRICON Conference, Vol 2.Piscataway(NJ):IEEE,1996,1006~1011
[54]于而铿.电力系统状态估计.北京:水利电力出版社,1985
[55]诸俊伟.电力系统分析.北京:中国电力出版社,1995
[56]王克英,穆刚,陈学允.计及PMU的状态估计精度分析及配置研究.中国电机工程学报,2001,21(8):29~33
[57]费业泰.误差理论与数据处理.北京:机械工业出版社,1981
[58]秦晓辉,毕天姝,杨奇逊.计及PMU的混合非线性状态估计新方法.电力系统自动化,2007,31(4):28~33
[59]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
[60] IEEE Std C37.118-2005. IEEE Standard for Synchrophasors for Power Systems. IEEE Power Engineering Society, 2005
[61]国家电网公司.电力系统实时动态监测系统技术规范.2005
[62]国家电网公司.国家电网公司先进适用技术评估报告-电网动态实时监测技术.2006
[63] Zhenyu Huang, John F. Hauer, and Kenneth E. Martin. Evaluation of PMU dynamic performance in both lab environments and under field operating conditions. IEEE Power Engineering Society General Meeting, Tampa, 24-28 Jun 2007:1-6
[64] J. F. Hauer, K. E. Martin, and Harry Lee. Evaluating the Dynamic Performance of Phasor Measurement Units: Experience in the Western Power System. WECC Disturbance Monitoring Work Group, June 15, 2004.
[65]刘辉乐,刘天琪,彭锦新.基于PMU的分布式电力系统动态状态估计新算法.电力系统自动化,2005,29(4):34~39
[66]卫志农,李阳林,郑玉平.基于混合量测的电力系统线性动态状态估计算法.电力系统自动化,2007,31(6):39~43
[67] A. S. Debs and R. E. Larson. A dynamic estimator for tracking the state of the power system. IEEE Trans. Power Apparat. Syst., 1970, 89 (7):1670–1678.
[68]张伯明,王世缨.电力系统动态状态估计中不正常事件的处理.中国电机工程学报,1993,13(3):52~58
[69] Kuang-Rong Shih and Shyh-Jier Huang. Application of a robust algorithm for dynamic state estimation of a power system. IEEE Trans. Power Syst., 2002, 17(1): 141~147
[70] Durgaprasad G., and Thakur S.S. Robust dynamic state estimation of power system based on M-estimation and realistic modeling of system dynamics. IEEE Trans. Power Syst., 1998, 13(4): 1331~1336
[71] J.S. Thorp, C.E. Seyler, A.G. Phadke. Electromechanical wave propagation in large electric power system. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 45, no. 6, June 1998: 614 ~ 622.
[72] R.M. Gardner, J.K. Wang, Y.Liu. Power System Event Location Analysis Using Wide-Area Measurement. IEEE Power Engineering Society General Meeting, Montreal, 18-22 Jun 2006:1~7.
[73] Z. Zhong, C.C. Xu, and B.J. Billian. Power system frequency monitoring network (FNET) implementation[J]. IEEE Transactions on Power Systems, vol. 20, no. 4, Nov, 2005: 1914– 1921.
[74] S.S. Tsai, L. Zhang. A.G. Phadke, et.al. Study of Global Frequency Dynamc Behavior of Large Power System[C]. IEEE Power System Conference and Exposition, vol. 1, 10-13 Oct,2004: 328~335
[75] M. Parashar,; J. S. Thorp, and C.E. Seyler. Continuum modeling of electromechanical dynamics in large-scale power systems[J]. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, Vol. 51, Issue 9, Sept. 2004: 1848 ~ 1858.
[76] S.S. Tsai, L. Zhang, A.G. Phadke, et.al. Frequency Sensitivity and Electromechanical Propagation Simulation Study in Large Power Systems. IEEE Transactions on Circuits and Systems I: regular papers, vol.54, no. 6, Aug, 2007: 1819– 1828.
[77] Jian Zuo, Mark Baldwin, Hengxu Zhang, et.al. Use of Frequency Oscillations to Improve Event Location Estimation in Power Systems[C]. IEEE Power Engineering Society General Meeting, Tampa, 24-28 Jun 2007: 1-7
[78]宋晓娜,毕天姝,吴京涛,等.基于WAMS的电网扰动识方法[J].电力系统自动化,2006,30(5):24~28.
[79]汪芳宗,陈德树,何仰赞.大规模电力系统暂态稳定性实时仿真及快速判断.中国电机工程学报,1993,13(6):13～19
[80]王成山,贾宏杰.一种寻找正确相关不稳定平衡点的基准方法.天津大学学报,1999,32(5):529～534
[81] A.M. Esklcioglu, O.Sevaioglu. Feasibility of lyapunov functions for power system transient stability analysis by the controlling UEP method. IEE Procedings-C,1992,139(2):152～156
[82] H. Yee, B.D. Spalding. Transient stability analysis of multi-machine systems by the method of hyperplanes. IEEE Trans on PAS, vol. PAS-96, 1977:276～284
[83]傅书逖.势能界面法(PEBS)暂态稳定分析的综述及展望.电力系统自动化,1998,22(9):16～18
[84]吕志来,张保会,哈恒旭.基于改进的势能界面判据实时预测电力系统稳定性.中国电机工程学报,2002,22(4):94～98
[85]吕志来,张保会,哈恒旭.提高暂态稳定计算效率的势能界面法.西安交通大学学报,2000,34(9):49～53
[86] K. Iimuma,T.Y. Ohtaka,S. Iwamoto.Preventive control with RIDGE theory considering n-th swing stability . IEEE/PES Transmission and Distribution Conference & Exhibition:Asia and Pacific,Yokohama,Janpan,2002:1554～1559
[87] J.Z. Tong, H.D. Chiang, T.P. Conneen. A sensitivity-based BCU method for fast derivation of stability limits in electric power systems. IEEE Transactions on Power Systems, 1993, 8(4):1418～1428
[88]江宁强,宋文忠,戴先中.基于稳定域边界的主导不稳定平衡点(BCU)法前提条件的验证.中国电机工程学报,2004,24(6):35～39
[89]薛禹胜.非自治非线性多刚体系统的稳定性分析.南京:江苏科学技术出版社,1999
[90] Chih-Wen Liu and James S. Thorp. New Methods for Computing Power System Dynamic Response for Real-Time Transient Stability Prediction. IEEE Transaction on Circuits and Systems-Ⅰ: Fundamental Theory and Applications, 47(3),2000:324~337.
[91] C. W. Liu, J. Thorp. Application of synchronized phasor measurements to real-time transient stability prediction. IEEE Proc-Gener Transm Distriib, 142(4),1995:355~360.
[92]吕志来,张保会,哈恒旭.基于PMU的电力系统暂态稳定实时快速预测的研究.继电器,2000,28(1):3～5
[93]苏建设,陈陈.基于GPS同步量测量的时间序列法暂态稳定预测.电力自动化设备.2001,21(9):7～9
[94]郭强,刘晓鹏,吕世荣,夏道止.GPS同步时钟用于电力系统暂态稳定性预测和控制.电力系统自动化,1998,22(6):11～13
[95] Y.J. Wang, C.W. Liu, L.D. Sue. A remedial control scheme protects against transient instabilities based on phasor measurement units 2000 Power Engineering Society Summer Meeting, Washington, USA, Jul. 2000:1191～1195
[96]彭疆南,孙元章,王海风.基于广域测量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
[97]张鹏飞,薛禹胜,张启平,励刚,曹路.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
[98] C.W. Liu, M.C. Su, S.S. Tsay, Y.J. Wang. Application of a novel fuzzy neural network to real-time transient stability swings prediction based on synchronized phasor measurements. IEEE Transactions on Power Systems,14(2):685~692
[99] S. Rovnyak, S. Kretsinger, J. Thorp, D. Brown.Decision trees for real-timetransient stability prediction. IEEE Transactions on Power Systems,1994,9(3):1417~1426
[100] I. Kamwa, R. Grondin, L. Loud. Time-varing contingency screening for dynamic security assessment using intelligent-systems techniques. IEEE Transactions on Power Systems,2001,16(3):526~536
[101] R.T.F. Ah King, H. C.S. Rughooputh. Real-time transient stability prediction using neural tree network. 1995 IEEE International Conference on Systems, Man and Cybernetics,Vol 3. Vancouver(BC, Canada):1995:2182~2187
[102]刘玉田,林飞.基于相量测量技术和模糊径向基网络的暂态稳定性预测.中国电机工程学报,2000,20(2):19~23
[103]林飞,刘玉田.基于模糊神经网络的电力系统暂态稳定控制决策.电工技术学报,2001,16(2):83~87
[104]赵磊,单渊达.基于轨迹信息的发电机暂态稳定指标分析方法.电网技术,2002,26(8):25~28
[105] H. Xie , B.H. Zhang. Power system transient stability detection based on characteristic concave or convex of trajectory. IEEE/PES Transmission and Distribution Conference & Exhibition:Asia and Pacific. Dalian, China. 2005:1～6
[106] Wang Liangcheng,Girgis A A.A new method for power system transient instability detection . IEEE Transactions on Power Delivery,12(3),1997: 1082-1089
[107]滕林,刘万顺,贠志皓,李贵存,俞波,滕云.电力系统暂态稳定实时紧急控制的研究.中国电机工程学报,2003,23(1):64～69
[108]沈善德.电力系统辨识.北京:清华大学出版社,1993
[109] Zhenyu Huang, Dmitry Kosterev and Ross Guttromson, etc. Model Validation with Hybrid Dynamic Simulation. IEEE 2006 Power Engineering Society General Meeting. 2006, 6,18-22,:1-9
[110]谢小荣,肖晋宇,李建.一种估计同步发电机功角的新方法.中国电机工程学报,2003,23(11):106-110
[111]严登俊,鞠平,吴峰,等.基于GPS时钟信号的发电机功角实时测量方法.电力系统自动化,2002,26(8):38-40
[112]李光琦.电力系统暂态分析.(第二版).北京:中国电力出版社,1995.
[113]杨奇逊,黄少锋.微型机继电保护基础(第二版).北京:中国电力出版社,2005
[114]国家电力调度通信中心.电网调度运行实用技术问答.北京:中国电力出版社,2000
[115]秦晓辉,毕天姝,杨奇逊.基于WAMS的电力系统机电暂态过程动态状态估计.中国电机工程学报.2008,28,(7):19~25
[116]薛禹胜.滑步与发散,运动系统与一般动力学系统-兼谢廖浩辉和唐云先生.电力系统自动化,2003,27(7):17～21
[117]邵振国,薛禹胜,陈关荣.一种并不导致失步的滑步现象.电力系统自动化,2003,27(24):6~9
[118]周海强,薛禹胜.稳定轨迹后续稳定性的预估.电力系统自动化,2002,26(4):1～5
[119]薛峰,丁纯,薛禹胜.数值积分自动终止的算法及其工程应用.电力系统自动化,2001,25(21):9～13
[2] D. Kosterev, S. Yirga, and V. Venkatasubramanian, Validation report of the August 10, 1996 WSCC disturbance, Operating Capability Study Group, Western Systems Coordinating Council, March 1997
[3]王梅义.有感于美国西部电网大停电.电网技术,1996,20(9):43~46
[4] Taylor C W, Erickson D C. Recording and Analyzing the July 2 cascading Outage, IEEE Computer Applications in Power, 1997, 10(1): 26~30.
[5]陈建业,王仲鸣.1996年夏季美国西部电力系统停电事故.国际电力,1998,3(2):52~56
[6]何大愚.对于美国西部电力系统的1996年7月2日大停电事故的初步认识.电网技术,1996,20(9):35~39
[7] R. Aggarwal, R. Daschmans, R. Schellberg, V. Venkatasubramanian, and S. Yirga, Validation studies of the July 2, 1996 WSCC system disturbance event, Operating Capability Study Group, Western Systems Coordinating Council, July 1997
[8] Kosterev D N, Taylor C W, Mittestadt W A, Model validation for the August 10, 1996 WSCC outage, IEEE Trans. on Power Systems, 1999, 14(3): 967~979
[9]卢卫星,舒印丝,史连军.美国西部电力系统1996年8月10日大停电事故.电网技术,1996,20(9):40~42
[10]甘德强,胡江溢,韩祯祥.2003年国际若干停电事故思考.电力系统自动化,2004,28(3):1~4.
[11] U.S.-Canada power systems outage task force final report on the august 14, 2003 blackout in the United States and Canada[R/OL]. http: //www.ferc.gov/, April, 2004
[12]薛禹胜.综合防御由偶然故障演化为电力灾难——北美“8·14”大停电的警示.电力系统自动化,2003,27(18):1~5
[13]印永华,郭剑波,赵建军,等.美加“8.14”大停电事故初步分析以及应吸取的教训[J].电网技术,2003,27(10):8~11
[14]何大愚.一年以后对美加“8.14”大停电事故的反思.电网技术,2004,28(21):1～5
[15]王伟.“8.14”美加大停电突显EMS实用化的正确性.华北电力技术,2004,7:35~36
[16]谢旭.从“8.14”美加大停电看电网调度自动化面临的挑战.华北电力技术,2004,7:37~41
[17]蔡敏,孙光辉,吴晓辰,等.稳定控制所用交流设备跳闸判据的分析及应用[J].电力系统自动化,2007,31(8):46~51.
[18] A. G. Phadke,“Synchronized Phasor Measurements in Power Systems”,IEEE Computer Applications in Power, 1993, 6(2),:10~15
[19] Burnett R O, Phadke A G, et al.Synchronized Phasor Measurements of a Power System Event. IEEE Trans on PS,1994(3):1643~1650
[20] Martin K E, Benmouyal G, Adamiak M G, et al. IEEE Standard for Synchrophasors for Power Systems. IEEE Transactions on Power Delivery, 1998, 13(1): 73– 77
[21] F.J.Marin, F.G.Lagos, G.Joya. Genetic Algorithms for Optimal Placement of Phasor Measurement Units in Electrical Networks. Electronics Letters, 39(19), Sept.2003
[22] B.Milosevic, M.Begovic. Nondominated Sorting Genetic Algorithm for Optimal Phasor Measurement Placement IEEE Trans. On Power Systems,18(1), Feb,2003:69~75
[23] R.F.Nuqui, A.G.Phadke. Phasor Measurement Unit Placement Based on Incomplete Observability IEEE Power Engineering Society Summer Meeting, 21~25 July 2002:2888~893
[24] A G Phadke. Synchronized Phasor Measurements - A Historical Overview. IEEE/PES Transmission and Distribution Conference and Exhibition: Asia Pacific, 2002, Vol.1: 476~479
[25] Bhargava B. Synchronized Phasor Measurement System project at Southern California Edison Co. IEEE Power Engineering Society Summer Meeting, July 1999, Vol.1:16– 22
[26]国家电网公司.国家电网公司“十一·五”科技发展规划.国家电网公司,2006.2
[27] L.Mili, T.Baldwin, R.Adapa. Phasor Measurement Placement for Voltage Stability Analysis of Power Systems. Proceeding of 29th Conference on Decision and Control. Honolulu,Hawaii.December 1990
[28] Phadke A G, Pickett B, Adamiak M, et a1. Synchronized Sampling and Phasor Measurements for Relaying and Control.IEEE Trans. on Power Delivery, 1994, 9(1) 442~452
[29]蔡运清,汪磊,Kip Morison,Prabha Kundur,周逢权,郭志忠.广域保护(稳控)技术的现状及展望.电网技术,2004,28(8):20～25
[30]中国电力科学研究院系统研究所.跨区电网动态稳定监控系统可行性研究.北京:中国电力科学研究院,2004.10
[31]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.2003,27(24):78～80
[32]许树楷,谢小荣,辛耀中.基于同步向量测量技术的广域测量系统应用现状及发展前景.电网技术,2005,29(2):44～49
[33]谢小荣,李红军,吴京涛,张涛,童陆园.同步相量技术应用于电力系统暂态稳定性控制的可行性分析.电网技术,2004,28(1):10～14
[34]薛禹胜,徐伟,Zhaoyang Dong.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
[35]常乃超,郭志忠.基于广域量测的全局非线性励磁控制.中国电机工程学报,2004,24(2):43~48
[36]张保会,谢欢,于广亮等.基于广域轨迹信息的多机系统暂态不稳定性快速预测方法.电网技术,2006,30(19):53~58
[37]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(2):38~45
[38]何飞跃,段献忠.基于广域测量的滑模TCSC控制器设计.电网技术,2006,30(23):50~55
[39]韩英铎,严剑峰,谢小荣.电力系统机电暂态过程主导动态参数的在线辨识.中国电机工程学报,2006,26(2):1~6
[40]丁军策,蔡泽祥,王克英.基于广域测量系统的状态估计研究综述.电力系统自动化,2006,30(7):98-103
[41] Phadke A G, Thorp J S, Karimi K J,et al. State Estimation with Phasor Measurements. IEEE Trans on Power Systems, 1986,1,(1):233~241
[42] Baldwin T L,Mili L Boison,M B etal. Power System Observability with Minimal Phasor Measurement Placement. IEEE Trans on Power Systems, 1993,8,(2):707~715
[43]卢志刚,许世范,史增洪,等.部分电压和电流相量可测量时电压相量的状态估计.电力系统自动化,2000,24(1):42~44
[44] W.M. Lin, J.H. Teng. State Estimation for Distribution Systems with Zero-injection Constraints, IEEE Transactions on Power Systems, 1996,11(1): 518~524
[45]程浩忠,袁青山,汪一华,等.基于等效电流量测变换的电力系统状态估计方法.电力系统自动化,2000,24(14):25~29
[46]丁军策,蔡泽祥,王克英.相量测量单元测量值对状态估计中等效电流量变换算法的影响.电网技术,2005,29(5):47~51
[47]丁军策,蔡泽祥,王克英.极坐标系下的快速等效电流量测变换状态估计方法.电力系统自动化,2005,29(5):31~33
[48]丁军策,蔡泽祥,王克英.基于广域测量系统的混合量测状态估计方法.中国电机工程学报,2006,26(2):58~63
[49]李强,周京阳,于尔铿,等.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
[50]李强,周京阳,于尔铿,等.基于相量量测的电力系统线性状态估计.电力系统自动化,2005,29(18):24~28
[51] Ming Zhou, Virgilio A. Centeno, James S. Thorp, et al. An Alternative for Including Phasor Measurements in State Estimators. IEEE Transactions on Power Systems, 2006,21(4): 1930~1937
[52] Thorp J S, Phadke A G, Karimi K J,et al. Real Time Voltage-phasor Measurements for Static State Estimation. IEEE Trans on Power System, 1986,1,(1):233~241
[53] Zivanovic R, Carnis C. Implementation of PMU Technology in Static State Estimation: an Overview. In Proceedings of 1996 IEEE AFRICON,4th AFRICON Conference, Vol 2.Piscataway(NJ):IEEE,1996,1006~1011
[54]于而铿.电力系统状态估计.北京:水利电力出版社,1985
[55]诸俊伟.电力系统分析.北京:中国电力出版社,1995
[56]王克英,穆刚,陈学允.计及PMU的状态估计精度分析及配置研究.中国电机工程学报,2001,21(8):29~33
[57]费业泰.误差理论与数据处理.北京:机械工业出版社,1981
[58]秦晓辉,毕天姝,杨奇逊.计及PMU的混合非线性状态估计新方法.电力系统自动化,2007,31(4):28~33
[59]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
[60] IEEE Std C37.118-2005. IEEE Standard for Synchrophasors for Power Systems. IEEE Power Engineering Society, 2005
[61]国家电网公司.电力系统实时动态监测系统技术规范.2005
[62]国家电网公司.国家电网公司先进适用技术评估报告-电网动态实时监测技术.2006
[63] Zhenyu Huang, John F. Hauer, and Kenneth E. Martin. Evaluation of PMU dynamic performance in both lab environments and under field operating conditions. IEEE Power Engineering Society General Meeting, Tampa, 24-28 Jun 2007:1-6
[64] J. F. Hauer, K. E. Martin, and Harry Lee. Evaluating the Dynamic Performance of Phasor Measurement Units: Experience in the Western Power System. WECC Disturbance Monitoring Work Group, June 15, 2004.
[65]刘辉乐,刘天琪,彭锦新.基于PMU的分布式电力系统动态状态估计新算法.电力系统自动化,2005,29(4):34~39
[66]卫志农,李阳林,郑玉平.基于混合量测的电力系统线性动态状态估计算法.电力系统自动化,2007,31(6):39~43
[67] A. S. Debs and R. E. Larson. A dynamic estimator for tracking the state of the power system. IEEE Trans. Power Apparat. Syst., 1970, 89 (7):1670–1678.
[68]张伯明,王世缨.电力系统动态状态估计中不正常事件的处理.中国电机工程学报,1993,13(3):52~58
[69] Kuang-Rong Shih and Shyh-Jier Huang. Application of a robust algorithm for dynamic state estimation of a power system. IEEE Trans. Power Syst., 2002, 17(1): 141~147
[70] Durgaprasad G., and Thakur S.S. Robust dynamic state estimation of power system based on M-estimation and realistic modeling of system dynamics. IEEE Trans. Power Syst., 1998, 13(4): 1331~1336
[71] J.S. Thorp, C.E. Seyler, A.G. Phadke. Electromechanical wave propagation in large electric power system. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 45, no. 6, June 1998: 614 ~ 622.
[72] R.M. Gardner, J.K. Wang, Y.Liu. Power System Event Location Analysis Using Wide-Area Measurement. IEEE Power Engineering Society General Meeting, Montreal, 18-22 Jun 2006:1~7.
[73] Z. Zhong, C.C. Xu, and B.J. Billian. Power system frequency monitoring network (FNET) implementation[J]. IEEE Transactions on Power Systems, vol. 20, no. 4, Nov, 2005: 1914– 1921.
[74] S.S. Tsai, L. Zhang. A.G. Phadke, et.al. Study of Global Frequency Dynamc Behavior of Large Power System[C]. IEEE Power System Conference and Exposition, vol. 1, 10-13 Oct,2004: 328~335
[75] M. Parashar,; J. S. Thorp, and C.E. Seyler. Continuum modeling of electromechanical dynamics in large-scale power systems[J]. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, Vol. 51, Issue 9, Sept. 2004: 1848 ~ 1858.
[76] S.S. Tsai, L. Zhang, A.G. Phadke, et.al. Frequency Sensitivity and Electromechanical Propagation Simulation Study in Large Power Systems. IEEE Transactions on Circuits and Systems I: regular papers, vol.54, no. 6, Aug, 2007: 1819– 1828.
[77] Jian Zuo, Mark Baldwin, Hengxu Zhang, et.al. Use of Frequency Oscillations to Improve Event Location Estimation in Power Systems[C]. IEEE Power Engineering Society General Meeting, Tampa, 24-28 Jun 2007: 1-7
[78]宋晓娜,毕天姝,吴京涛,等.基于WAMS的电网扰动识方法[J].电力系统自动化,2006,30(5):24~28.
[79]汪芳宗,陈德树,何仰赞.大规模电力系统暂态稳定性实时仿真及快速判断.中国电机工程学报,1993,13(6):13～19
[80]王成山,贾宏杰.一种寻找正确相关不稳定平衡点的基准方法.天津大学学报,1999,32(5):529～534
[81] A.M. Esklcioglu, O.Sevaioglu. Feasibility of lyapunov functions for power system transient stability analysis by the controlling UEP method. IEE Procedings-C,1992,139(2):152～156
[82] H. Yee, B.D. Spalding. Transient stability analysis of multi-machine systems by the method of hyperplanes. IEEE Trans on PAS, vol. PAS-96, 1977:276～284
[83]傅书逖.势能界面法(PEBS)暂态稳定分析的综述及展望.电力系统自动化,1998,22(9):16～18
[84]吕志来,张保会,哈恒旭.基于改进的势能界面判据实时预测电力系统稳定性.中国电机工程学报,2002,22(4):94～98
[85]吕志来,张保会,哈恒旭.提高暂态稳定计算效率的势能界面法.西安交通大学学报,2000,34(9):49～53
[86] K. Iimuma,T.Y. Ohtaka,S. Iwamoto.Preventive control with RIDGE theory considering n-th swing stability . IEEE/PES Transmission and Distribution Conference & Exhibition:Asia and Pacific,Yokohama,Janpan,2002:1554～1559
[87] J.Z. Tong, H.D. Chiang, T.P. Conneen. A sensitivity-based BCU method for fast derivation of stability limits in electric power systems. IEEE Transactions on Power Systems, 1993, 8(4):1418～1428
[88]江宁强,宋文忠,戴先中.基于稳定域边界的主导不稳定平衡点(BCU)法前提条件的验证.中国电机工程学报,2004,24(6):35～39
[89]薛禹胜.非自治非线性多刚体系统的稳定性分析.南京:江苏科学技术出版社,1999
[90] Chih-Wen Liu and James S. Thorp. New Methods for Computing Power System Dynamic Response for Real-Time Transient Stability Prediction. IEEE Transaction on Circuits and Systems-Ⅰ: Fundamental Theory and Applications, 47(3),2000:324~337.
[91] C. W. Liu, J. Thorp. Application of synchronized phasor measurements to real-time transient stability prediction. IEEE Proc-Gener Transm Distriib, 142(4),1995:355~360.
[92]吕志来,张保会,哈恒旭.基于PMU的电力系统暂态稳定实时快速预测的研究.继电器,2000,28(1):3～5
[93]苏建设,陈陈.基于GPS同步量测量的时间序列法暂态稳定预测.电力自动化设备.2001,21(9):7～9
[94]郭强,刘晓鹏,吕世荣,夏道止.GPS同步时钟用于电力系统暂态稳定性预测和控制.电力系统自动化,1998,22(6):11～13
[95] Y.J. Wang, C.W. Liu, L.D. Sue. A remedial control scheme protects against transient instabilities based on phasor measurement units 2000 Power Engineering Society Summer Meeting, Washington, USA, Jul. 2000:1191～1195
[96]彭疆南,孙元章,王海风.基于广域测量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
[97]张鹏飞,薛禹胜,张启平,励刚,曹路.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
[98] C.W. Liu, M.C. Su, S.S. Tsay, Y.J. Wang. Application of a novel fuzzy neural network to real-time transient stability swings prediction based on synchronized phasor measurements. IEEE Transactions on Power Systems,14(2):685~692
[99] S. Rovnyak, S. Kretsinger, J. Thorp, D. Brown.Decision trees for real-timetransient stability prediction. IEEE Transactions on Power Systems,1994,9(3):1417~1426
[100] I. Kamwa, R. Grondin, L. Loud. Time-varing contingency screening for dynamic security assessment using intelligent-systems techniques. IEEE Transactions on Power Systems,2001,16(3):526~536
[101] R.T.F. Ah King, H. C.S. Rughooputh. Real-time transient stability prediction using neural tree network. 1995 IEEE International Conference on Systems, Man and Cybernetics,Vol 3. Vancouver(BC, Canada):1995:2182~2187
[102]刘玉田,林飞.基于相量测量技术和模糊径向基网络的暂态稳定性预测.中国电机工程学报,2000,20(2):19~23
[103]林飞,刘玉田.基于模糊神经网络的电力系统暂态稳定控制决策.电工技术学报,2001,16(2):83~87
[104]赵磊,单渊达.基于轨迹信息的发电机暂态稳定指标分析方法.电网技术,2002,26(8):25~28
[105] H. Xie , B.H. Zhang. Power system transient stability detection based on characteristic concave or convex of trajectory. IEEE/PES Transmission and Distribution Conference & Exhibition:Asia and Pacific. Dalian, China. 2005:1～6
[106] Wang Liangcheng,Girgis A A.A new method for power system transient instability detection . IEEE Transactions on Power Delivery,12(3),1997: 1082-1089
[107]滕林,刘万顺,贠志皓,李贵存,俞波,滕云.电力系统暂态稳定实时紧急控制的研究.中国电机工程学报,2003,23(1):64～69
[108]沈善德.电力系统辨识.北京:清华大学出版社,1993
[109] Zhenyu Huang, Dmitry Kosterev and Ross Guttromson, etc. Model Validation with Hybrid Dynamic Simulation. IEEE 2006 Power Engineering Society General Meeting. 2006, 6,18-22,:1-9
[110]谢小荣,肖晋宇,李建.一种估计同步发电机功角的新方法.中国电机工程学报,2003,23(11):106-110
[111]严登俊,鞠平,吴峰,等.基于GPS时钟信号的发电机功角实时测量方法.电力系统自动化,2002,26(8):38-40
[112]李光琦.电力系统暂态分析.(第二版).北京:中国电力出版社,1995.
[113]杨奇逊,黄少锋.微型机继电保护基础(第二版).北京:中国电力出版社,2005
[114]国家电力调度通信中心.电网调度运行实用技术问答.北京:中国电力出版社,2000
[115]秦晓辉,毕天姝,杨奇逊.基于WAMS的电力系统机电暂态过程动态状态估计.中国电机工程学报.2008,28,(7):19~25
[116]薛禹胜.滑步与发散,运动系统与一般动力学系统-兼谢廖浩辉和唐云先生.电力系统自动化,2003,27(7):17～21
[117]邵振国,薛禹胜,陈关荣.一种并不导致失步的滑步现象.电力系统自动化,2003,27(24):6~9
[118]周海强,薛禹胜.稳定轨迹后续稳定性的预估.电力系统自动化,2002,26(4):1～5
[119]薛峰,丁纯,薛禹胜.数值积分自动终止的算法及其工程应用.电力系统自动化,2001,25(21):9～13
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |