Abstract：Phasor measurement unit (PMU) can measure the rotor angle of synchronous machine in power system dynamic process. However, the bad data may decrease the accuracy of state estimations, even lead to the failure of the estimator. Based on the robust cubature Kalman filter (CKF), a novel dynamic state estimator for synchronous machine in the electromechanical transient process is proposed. A time-varying multi-dimensional scale factor is introduced into CKF. The PMU measure- ment covariance can be adjusted according to the innovation. As a result, the PMU measurements will correct the state predictions precisely. The formulation of the scale factor is clarified, and the method for dealing with the problem of the gain matrix singularity is addressed. The detailed process of dynamic state estimation based on robust CKF is given. The simulation results show that the method can prevent the influence of bad data on the precision of the dynamic state estimation.
毕天姝, 陈亮, 薛安成, 杨奇逊. 基于鲁棒容积卡尔曼滤波器的发电机动态状态估计[J]. 电工技术学报, 2016, 31(4): 163-169.
Bi Tianshu, Chen Liang, Xue Ancheng, Yang Qixun. Dynamic State Estimator for Synchronous Machines Based on Robust Cubature Kalman Filter. Transactions of China Electrotechnical Society, 2016, 31(4): 163-169.
[1] Phadke A G. Synchronized phasor measurements in power systems[J]. IEEE Computer Applications in Power, 1993, 6(2): 10-15. [2] Burnett R O, Phadke A G, et al. Synchronized phasor measurements of a power system event[J]. IEEE Trans- actions on Power System, 1994, 9(3): 1643-1650. [3] Phadke A G. Synchronized phasor measurements-a historical overview[C]//IEEE/PES Transmission and Distribution Conference and Exhibition: Asia Pacific, 2002, 1: 476-479. [4] 秦晓辉, 毕天姝, 杨奇逊, 等. 基于WAMS动态轨迹的电力系统功角失稳判据[J]. 电力系统自动化, 2008, 32(23): 18-22. Qin Xiaohui, Bi Tianshu, Yang Qixun, et al. Power system transient stability assessment based on WAMS dynamic trajectories[J]. Automation of Electric Power Systems, 2008, 32(23): 18-22. [5] 徐慧明, 毕天姝, 黄少锋, 等. 基于WAMS的潮流转移识别算法[J]. 电力系统自动化, 2006, 30(14): 14-19. Xu Huiming, Bi Tianshu, Huang Shaofeng, et al. WAMS based flow transfer identification algrithm[J]. Automation of Electric Power Systems, 2006, 30(14): 14-19. [6] 杨东俊, 丁坚勇, 邵汉桥, 等. 基于WAMS的负阻尼低频振荡与强迫功率振荡的特征判别[J]. 电力系统自动化, 2013, 37(13): 57-62. Yang Dongjun, Ding Jianyong, Shao Hanqiao, et al. WAMS based characteristic discrimination of negative damping low-frequency oscillation and forced power oscillation[J]. Automation of Electric Power Systems, 2013, 37(13): 57-62. [7] 宋洪磊, 吴俊勇, 郝亮亮, 等. 基于WAMS和改进拉普拉斯特征映射的同调机群在线识别[J]. 电网技术, 2013, 37(8): 2157-2164. Song Honglei, Wu Junyong, Hao Liangliang, et al. On-line identification of coherent generator based on WAMS and improved Laplacian eigenmap algorithm[J]. Power System Technology, 2013, 37(8): 2157-2164. [8] 马世英, 刘道伟, 吴萌, 等. 基于WAMS及机组对的电网暂态稳定态势在线量化评估方法[J]. 电网技术, 2013, 37(5): 1323-1328. Ma Shiying, Liu Daowei, Wu Meng, et al. An online quantitative evaluation method of power system transient stability situation based on WAMS and generator pair[J]. Power System Technology, 2013, 37(5): 1323-1328. [9] 丁涛, 董柏峰, 顾伟, 等. 基于PMU 的电压稳定动态线性化指标优化切负荷算法[J]. 电力系统保护与控制, 2013, 41(9): 27-33. Ding Tao, Dong Baifeng, Gu Wei, et al. Optimization of a load shedding scheme using dynamic voltage stability linearized index based on PMU[J]. Power System Protection and Control, 2013, 41(9): 27-33. [10] 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[J]. 中国电机工程学报, 2008, 28(7): 19-25. Qin Xiaohui, Bi Tianshu, Yang Qixun. Dynamic state estimator based on WAMS during power system transient process[J]. Proceedings of the CSEE, 2008, 28(7): 19-25. [11] Huang Zhenyu, Schneider K, Nieplocha J. Feasibility studies of applying kalman filter techniques to power system dynamic state estimation[C]//International Conference on Power Engineering, 2007: 376-382. [12] Ghahremani E, Kamwa I. Dynamic state estimation in power system by applying the extended Kalman filter with unknown inputs to phasor measurements[J].IEEE Transations on Power Systems, 2011, 26(4): 2556-2565. [13] Ghahremani E, Kamwa I. Online state estimation of a synchronous generator using unscented Kalman filter from phasor measurements units[J]. IEEE Transactions on Energy Conversion, 2011, 26(4): 1099-1108. [14] Wang Shaobu, Gao Wenzhong, Meliopoulos A P S. An alternative method for power system dynamic state estimation based on unscented transform[J]. IEEE Transactions on Power System, 2012, 27(2): 942-950. [15] Arasaratnam I, Haykin S. Cubature Kalman filters[J]. IEEE Transactions on Automatic Control, 2009, 54(6): 1254-1269. [16] Arasaratnam I, Haykin S, Hurd T R. Cubature Kalman filter for continuous-discrete systems: theory and simulations[J]. IEEE Transactions on Signal Pro- cessing, 2010, 58(10): 4977-4993. [17] 巨云涛, 吴文传, 张伯明. 支持大规模电流量测的配网抗差状态估计方法[J]. 中国电机工程学报, 2011, 31(19): 82-89. Ju Yuntao, Wu Wenchuan, Zhang Boming. A new method for distributed state estimation accommodating current measurements[J]. Proceedings of the CSEE, 2011, 31(19): 82-89. [18] 李碧君, 薛禹胜, 顾锦汶, 等. 基于快速分解正交变换状态估计算法的坏数据检测与辨识[J]. 电力系统自动化, 1999, 23(20): 1-4. Li Bijun, Xue Yusheng, Gu Jinwen, et al. Detection and identification of bad data in state estimation using fast decoupled orthogonal transformation[J]. Automation of Electric Power Systems, 1999, 23(20): 1-4. [19] Shih K R, Huang S J. Application of a robust algorithm for dynamic state estimation of a power system[J]. IEEE Transaction on Power System, 2002, 17(1): 141-147.
2016, Vol. 31 
