标题：A filtering algorithm to dynamic state estimation for power systems with sensor delay
作者：Cheng, Cheng ;Bai, Xingzhen ;Chen, Xiangmin
作者机构：[Cheng, Cheng ;Bai, Xingzhen ;Chen, Xiangmin ] Dept. College of Electrical Engineering and Automation, Shandong University of Science and Technology, 更多
会议名称：2017 Chinese Automation Congress, CAC 2017
会议日期：October 20, 2017 - October 22, 2017
来源：Proceedings - 2017 Chinese Automation Congress, CAC 2017
摘要：In this paper, a recursive filtering method based on Kalman filter is proposed for the sensor delay in each state measurement of power system. Due to sampling frequency in the power system is generally high in milliseconds, the network topology is unchanged and the system state does not change much, therefore the system state at the next moment can be approximately linear relationship with the current state of the system, so we can get the linear state equation. In the measurement, the sensor delay is a common phenomenon in the project, in order to solve this problem in the dynamic estimation of the power system, a reasonable observation model is established to make it more close to the actual measurement situation in this paper, where the delay variable satisfies the Bernoulli distribution. Moreover, assume that the noise is Gaussian white noise, and then on the basis of two equations, using Kalman filter and some mathematical methods to find the gain parameters under the minimum error, make the filtering algorithm complete. Simulations are carried out on the IEEE 5-bus test system. The simulation results shows that the effectiveness of the proposed filtering algorithm.
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