Abstract：Generator dynamic state estimation (DSE) provides important parameters in dynamic monitor and control system of power system. But there are some problems of low filtering accuracy even filter divergence caused by the asymmetric or non-positive covariance matrix in CKF recursive process. This paper put forward the equations of generation DSE based on square root cubature Kalman filter (SRCKF). Wherein, the square root filtering (SRF) is also combined with, to ensure the non-negative definite covariance matrix. Finally, the generation DSE based on SRCKF, CKF and UKF was realized in IEEE 14-node system and actual system respectively. The results prove SRCKF can solve the filtering divergence caused by non-positive definite covariance matrix in CKF. Moreover, the simulation shows that the efficiency, the filtering performance and the numerical stability of SRCKF are superior to the CKF and UKF methods.
安军, 杨振瑞, 周毅博, 桂建忠, 石岩. 基于平方根容积卡尔曼滤波的发电机动态状态估计[J]. 电工技术学报, 2017, 32(12): 234-240.
An Jun, Yang Zhenrui, Zhou Yibo, Gui Jianzhong, Shi Yan. Dynamic State Estimator for Synchronous-Machines Based on Square Root Cubature Kalman Filter. Transactions of China Electrotechnical Society, 2017, 32(12): 234-240.
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