Robust dynamic state estimation of power systems with model uncertainties based on adaptive unscented H-infinity filter
Robust dynamic state estimation of power systems with model uncertainties based on adaptive unscented H-infinity filter
复制标题
基于自适应无迹H无穷滤波器的模型不确定性电力系统鲁棒动态状态估计
DOI：
10.1049/iet-gtd.2019.0031
复制
发表时间：
2019
影响因子：
2.5
通讯作者：
Nan Dongliang
中科院分区：
文献类型：
--
作者：
Wang Yi;Sun Yonghui;Dinavahi Venkata;Wang Kaike;Nan Dongliang
This study considers the dynamic state estimation of power systems with model uncertainties that might be caused by the unknown noise statistics or unpredicted changes to the model parameters. To deal with these issues, an innovation‐based estimator that is able to dynamically revise the statistics of system and measurement noise is proposed firstly. Then, based on the criteria for bounding the adverse influences on the estimation error of model uncertainties and unscented transform technique, an adaptive strategy is developed to adjust the estimation error covariance matrix under various conditions. Finally, by incorporating the proposed approaches and filter theory, a novel adaptive unscented filter is established to realise dynamic state estimation of power system against model uncertainties. Extensive simulation results obtained from the IEEE‐39 bus test system are presented to illustrate the effectiveness and robustness of the proposed method.
