Three-phase Dynamic State Estimation for Distribution Network in Event-triggered Mechanism

被引：0

作者：

Huang M. ^{[1
]}

Xu Q. ^{[1
]}

Sun G. ^{[1
]}

Wei Z. ^{[1
]}

Sun K. ^{[1
]}

机构：

[1] School of Electrical and Power Engineering, Hohai University, Nanjing

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 13期

基金：

中国国家自然科学基金;

关键词：

distribution system; ensemble Kalman filter; event-triggered mechanism; state estimation; weighted least squares method;

D O I：

10.7500/AEPS20231106005

中图分类号：

学科分类号：

摘要：

With the development of advanced metering infrastructure and the wide application of smart meters, the rich terminal measurement information is provided for the three-phase state estimation of distribution networks. At the same time, a large amount of smart meter data puts forward higher communication bandwidth and real-time storage requirements to the communication system of distribution networks. In order to alleviate the phenomenon of the measurement congestion and delay, this paper introduces an event-triggered mechanism instead of the traditional periodic sampling of measurement data, which ensures the timely uploading of effective measurement information while reducing the communication cost and investment. On this basis, for the real-time state sensing problem of distribution network, this paper proposes a three-phase dynamic state estimation method based on the robust ensemble Kalman filter, which can maintain estimation accuracy similar to the weighted least squares method in normal operation scenarios. The method also possesses strong robustness against bad data. © 2024 Automation of Electric Power Systems Press. All rights reserved.

引用

页码：100 / 108

页数：8

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