@inproceedings{95d2331476494250b95616aa9b7faadb,
title = "Modified Kalman Filtering Method to Reduce the Error of Power Grid Impedance Online Estimation",
abstract = "In the power electric based power system, the grid impedance may change over time, which seriously affects the control and stability of the grid-connected converters. The existing methods usually had used Kalman filter method to detect the real grid impedance in real time. However, there is always a certain error between the estimated result and the true value. This article first establishes the Kalman observation model, and then analyzes the reason for the Kalman filter observation error. In order to eliminate the Kalman filter observation error as much as possible, a new method of predicting the grid impedance error, that is, the univariate linear regression method, can make the grid impedance value more accurate. Simulation has verified the effectiveness of the method.",
keywords = "grid impedance estimation, error model, Kalman filter, LCL-filter, online estimation",
author = "Yanqi Cheng and Weimin Wu and Henry Chung and Frede Blaabjerg and Koutroulis Eftychios and Lixun Zhu",
year = "2021",
month = may,
doi = "10.1109/ECCE-Asia49820.2021.9479087",
language = "English",
isbn = "978-1-7281-6345-1",
series = "International Conference on Power Electronics",
publisher = "IEEE Press",
pages = "2163--2168",
booktitle = "Proceedings of the 2021 IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCE-Asia)",
note = " 2021 IEEE 12th Energy Conversion Congress & Exposition - Asia (ECCE-Asia) ; Conference date: 24-05-2021 Through 27-05-2021",
}