Estimating Dynamic Model Parameters for Adaptive Protection and Control in Power System
Estimating Dynamic Model Parameters for Adaptive Protection and Control in Power System
复制标题
DOI：
10.1109/tpwrs.2014.2331317
复制
发表时间：
2015-07
影响因子：
6.6
通讯作者：
M. Ariff;B. Pal;A. K. Singh
中科院分区：
文献类型：
--
作者：
M. Ariff;B. Pal;A. K. Singh
本文提出了一种实时估计电力系统暂态稳定模型重要参数（如惯性常数 H 和直轴暂态电抗 xd'）的新方法。它在相量测量单元 (PMU) 数据上使用无迹卡尔曼滤波器 (UKF) 的变体。这些参数的准确估计对于评估振荡继电器的稳定性和调整自适应保护系统非常重要。 16机68总线系统模型的仿真数据证明了该方法的有效性。论文还对 UKF 和 EKF 方法在参数估计方面的性能进行了比较。在实际 PMU 数据中可能存在噪声的情况下，进一步验证了方法的稳健性。
This paper presents a new approach in estimating important parameters of power system transient stability model such as inertia constant H and direct axis transient reactance xd' in real time. It uses a variation of unscented Kalman filter (UKF) on the phasor measurement unit (PMU) data. The accurate estimation of these parameters is very important for assessing the stability and tuning the adaptive protection system on power swing relays. The effectiveness of the method is demonstrated in a simulated data from 16-machine 68-bus system model. The paper also presents the performance comparison between the UKF and EKF method in estimating the parameters. The robustness of method is further validated in the presence of noise that is likely to be in the PMU data in reality.