基于平方根UPF的电力系统鲁棒预测状态估计

Robust Forecasting State Estimation of Power System Based on Square Root UPF

针对辅助预测状态估计器在迭代计算中会出现状态预测误差协方差矩阵不正定,导致估计精度差甚至发散的问题,提出了基于平方根UPF的电力系统鲁棒辅助预测状态估计。该方法采用两种数学方法:矩阵Cholesky分解因子更新和矩阵QR分解,引入平方根技术动态更新状态预测误差协方差矩阵以保持状态预测误差协方差矩阵的正定性。运用MATLAB进行仿真模拟测试,结果表明:IEEE 30节点系统非高斯噪声测试中,平方根UPF电压相角的均方根误差平均值为UPF相应测试值的0.09%,平方根UPF电压幅值的均方根误差平均值为UPF相应测试值的0.14%;IEEE 57节点系统非高斯噪声测试中,平方根UPF电压相角的均方根误差平均值为UPF相应测试值的0.67%,平方根UPF电压幅值的均方根误差平均值为UPF相应测试值的0.57%。所提出的平方根UPF对解决辅助预测状态估计中状态预测误差协方差矩阵不正定的问题具有很好的效果,具有更高估计精度和鲁棒性。

In order to solve the problem of poor estimation accuracy and even divergence coused by the covariance matrix of state prediction error in iterative computation of forecasting-aided state estimators,in this study,a robust forecasting-aided state estimation for power systems based on SRUPF(square root unscented particle filter)was proposed.Two mathematical methods,matrix QR decomposition and matrix Cholesky factor update were adopted,and square root technology were introduced to dynamically update the state covariance matrix,thereby maintaining the positive definiteness of the state prediction error covariance matrix.The results of testing using MATLAB showed that in the non Gaussian noise testing of IEEE 30 systems,the average root mean square error of the SRUPF voltage phase angle was 0.09%of the corresponding test value of UPF,and the average root mean square error of the SRUPF voltage amplitude was 0.14%of the corresponding test value of UPF.In the IEEE 57 system non Gaussian noise test,the average root mean square error of the SRUPF voltage phase angle was 0.67%of the corresponding test value of the UPF,and the average root mean square error of the SRUPF voltage amplitude was 0.57%of the corresponding test value of the UPF.The SRUPF proposed in this paper had a good effect on solving the problem of non positive of the covariance matrix of state prediction errors in auxiliary predictive state estimation,with high estimation accuracy and robustness.