考虑量测相关性的容积卡尔曼滤波动态状态估计

针对电力系统动态状态估计中SCADA量测量间存在相关性的实际情况,文中提出了一种考虑量测相关性的容积卡尔曼滤波动态状态估计方法。首先进行了SCADA量测相关性分析,然后基于状态转移方程推导过程噪声协方差矩阵,基于容积变换方法计算考虑SCADA量测相关性的量测误差协方差矩阵,并提出了考虑量测相关性的电力系统动态状态估计流程,每次估计实时修正量测误差协方差矩阵及过程噪声协方差矩阵。IEEE-39节点系统的仿真结果表明,相较于不考虑量测相关性的容积卡尔曼滤波算法,文中方法能够明显提高状态估计结果的精度。

Dynamic state estimation of power system based on cubature kalman filter considering measurement correlation

Aiming at the situation that there are correlations among SCADA measurements, this paper proposes a cubature kalman filter method for power system dynamic state estimation considering SCADA measurement correlation. First, this paper analyses the reason of measurement correlation. Then the process noise covariance matrix is derived through state transition equation, and cubature transformation is used to calculate the measurement error covariance matrix. The dynamic state estimation process of power system considering measurement correlation is proposed, and the measurement error covariance matrix and process noise covariance matrix are corrected in real time for each estimation. The simulation results on IEEE-39 system demonstrate that the proposed method can significantly improve the accuracy of state estimation results compared with the cubature kalman filter algorithm without considering measurement correlation.