郑州大学学报（工学版）2024，Vol.45Issue(3)：119-126,142,9.DOI:10.13705/j.issn.1671-6833.2023.06.005
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
摘要
Abstract
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 corre-sponding 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.关键词
电力系统/无迹粒子滤波/鲁棒辅助预测状态估计/不正定性/平方根UPFKey words
power system/unscented particle filter/robust forecasting-aided state estimation/non-positive/SRUPF分类
信息技术与安全科学引用本文复制引用
王要强,赵楷,王义,王克文,梁军..基于平方根UPF的电力系统鲁棒预测状态估计[J].郑州大学学报（工学版）,2024,45(3):119-126,142,9.基金项目
国家自然科学基金资助项目(62203395) （62203395）
河南省博士后科研启动项目(202101011) （202101011）
