Abstract：The synchronized phasor estimation algorithm is the core of the synchronized phasor measurement technology. So it is very important to improve the measurement accuracy and the dynamic performance of the algorithm in the power system dynamic condition. A dynamic phasor estimation algorithm is proposed in this paper based on strong tracking Taylor-Kalman filter (STKF). First, taken into account the impacts of harmonics and measurement as well as the time-varying characteristics of amplitude or phase, a state space model of dynamic electrical signals is established. Since the Taylor- Kalman filter (TKF) fails to fast track the system parameters mutation when estimating the state variables, the idea of strong tracking filter was introduced, where the estimation covariance matrix can be adjusted adaptively according to the mismatch degree between the theoretical and the actual residual. This change improved the ability of the traditional Kalman filter to track mutation signal. Test results of both numerical signal with noise and fault voltage signal generated by Matlab/Simulink show that the STKF algorithm has better step response performance, measurement accuracy and stability than the TKF algorithm.
[1] 徐岩, 应璐曼, 王增平. 基于最大树理论的分阶段相量测量单元配置方案[J]. 电工技术学报, 2016, 31(4): 155-162. Xu Yan, Ying Luman, Wang Zengping. Staged phasor measurement unit placement algorithm based on theory of maximum tree[J]. Transactions of China Electrotechnical Society, 2016, 31(4): 155-162. [2] 李婷, 吴敏, 何勇. 计及广域测量系统时滞影响的灵活交流输电系统阻尼控制器多目标设计[J]. 电工技术学报, 2014, 29(8): 227-234. Li Ting, Wu Min, He Yong. Multi-objective design of FACTS damping controller based on wams with signal transmission delay[J]. Transactions of China Electrotechnical Society, 2014, 29(8): 227-234. [3] 李俊刚, 张爱民, 张杭, 等. 广域保护系统数据网络可靠性评估[J]. 电工技术学报, 2015, 30(12): 344-350. Li Jungang, Zhang Aimin, Zhang Hang, et al. Reliability evaluation of the wide area protect system[J]. Transactions of China Electrotechnical Society, 2015, 30(12): 344-350. [4] 麦瑞坤. 电力系统动态同步相量估计算法及其应用研究[D]. 成都: 西安交通大学, 2010. [5] 谢潇磊, 刘亚东, 孙鹏. 新型配电网线路PMU装置的研制[J]. 电力系统及其自动化, 2016, 40(12): 15-20. Xie Xiaolei, Liu Yadong, Sun Peng, et al. Development of novel PMU device for distribution network lines[J]. Automation of Electric Power System, 2016, 40(12): 15-20. [6] Von Meier A, Culler D, Mc Eachern A, et al. Micro-synchrophasors for distribution systems[C]// 2014 IEEE PES Inovative Smart Grid Technologies Conference (ISGT), Washington DC, USA: IEEE, 2014: 1-5. [7] Jose Antonio de la O Serna. Dynamic phasor estimates for power system oscillations[J]. IEEE Transactions on Instrumentation and Measurement, 2007, 56(5): 1648-1657. [8] Platas-Garza M A, Jose Antonio de la O Serna. Dynamic phasor and frequency estimates through maximally flat differentiators[J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(7): 1803-1810. [9] 麦瑞坤, 何振友, 薄志谦. 基于泰勒展开模型的同步相量估计新算法[J]. 电力系统自动化, 2008, 32(12): 22-26. Mai Ruikun, He Zhengyou, Bo Zhiqian. Research on Synchrophasor estimation algorithm based on taylor expansion[J]. Automation of Electric Power Systems, 2008, 32(2): 22-26. [10] Mai Ruikun, He Zhengyou, Fu Ling,et al. A dynamic synchrophasor estimation algorithm for online appli- cation[J]. IEEE Transactions on Power Delivery, 2010, 25(2): 570-578. [11] 符玲, 韩文朕. 基于频域动态模型的同步相量测量算法[J]. 中国电机工程学报, 2015, 35(6): 1371-1378. Fu Ling, Han Wenzhen. Dynamic phasor estimator based on frequency domain model[J]. Proceeding of the CSEE, 2015, 35(6): 1371-1378. [12] 符玲, 韩文朕, 麦瑞坤, 等. 基于时频信息的动态同步相量测量算法[J]. 中国电机工程学报, 2015, 35(6): 1371-1378. Fu Ling, Han Wenzhen, Mai Ruikun, et al. Time- frequency information-based dynamic phasor estimator[J]. Proceeding of the CSEE, 2015, 35(6): 1371-1378. [13] Jose Antonio de la O Serna, Maldonado J R. Instantaneous oscillating phasor estimates with Taylor-Kalman filters[J]. IEEE Transactions on Power Systems, 2011, 26(4): 2336-2344. [14] 吴智力, 赵庆生. 低频采样下基于卡尔曼滤波的同步相量测量算法的研究[J]. 电力系统保护与控制, 2014, 42(15): 94-99. Wu Zhili, Zhao Qingsheng. A Kalman-filter based phasor measurement algorithm under low sampling frequency[J]. Power System Protection and Control, 2014, 42(15): 94-99. [15] IEEE Std C37.118.1—2011 IEEE Standard for Synchrophasor for Power Systems[S]. 2011. [16] 李江, 王义伟. 卡尔曼滤波理论在电力系统中的应用综述[J]. 电力系统保护与控制, 2014, 42(6): 135- 144. Li Jiang, Wang Yiwei. A survey on the application of Kalman filtering method in power system[J]. Power System Protection and Control, 2014, 42(6): 135-144. [17] Girgis A. A new Kalman filtering based digital distance relay[J]. IEEE Transactions on Power Application System, 1982, 101(9): 3471-3480. [18] Wood H C, Ohnson N, Sachdev M. Kalman filtering applied to power system measurements relaying[J]. IEEE Transactions on Power Application System, 1985, 104(12): 3565-3573. [19] 赵仁德, 马帅. 基于强跟踪滤波器的电力系统频率测量算法[J]. 电力系统保护与控制, 2013, 41(7): 85-90. Zhao Rende, Ma Shuai. Strong tracking filter based frequency-measuring algorithm for power system[J]. Power System Protection and Control, 2013, 41(7): 85-90. [20] 周东华, 席裕庚, 张仲俊. 非线性系统带次优渐消因子的扩展卡尔曼滤波[J]. 控制与决策, 1990, 5(5): 1-6. Zhou Donghua, Xi Yugeng, Zhang Zhongjun. Subop- timal fading extended Kalman filter for nonlinear systems[J]. Control and Decision, 1990, 5(5): 1-6.
2018, Vol. 33 
