Robust Forecasting-aided State Estimation Considering Uncertainty in Distribution System

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外文摘要：With the development of the smart grid,the distri-bution system operation conditions become more complex and changeable.Furthermore,due to the influence of observation outliers and uncertain noise statistics,it is more difficult to grasp the dynamic operation characteristics of distribution system.In order to address these problems,by using projection statistics and the noise covariance updating technology based on the Sage-Husa noise estimator,for distribution power system with outliers and uncertain noise statistics,a robust adaptive cubature Kalman filter forecasting-aided state estimation method is proposed based on generalized-maximum likelihood type estimator.Furthermore,an adaptive strategy,which can enhance the filtering accuracy under normal conditions,is presented.In the simulation part,the branch parameters and node load parameters of the test system are appropriately modified to simulate the asymmetry of the three-phase branch parameters and the asymmetry of the three-phase loads.Finally,through simulation experiments on the improved test system,it is verified that the robust forecasting-aided state estimation method,presented in this paper,can effectively perceive the actual operating state of the distribution network in different simulation scenarios.

外文关键词：

Cubature Kalman filterdistribution power systemforecasting-aided state estimationprojection statistics

作者：

Dongchen Hou、Yonghui Sun、Linchuang Zhang、Sen Wang

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作者单位：

College of Energy and Electrical Engineering,Hohai University,Nanjing 210098,China

基金：

National Natural Science Foundation of ChinaNational Natural Science Foundation of China-State Grid Joint Fund for Smart GridSix Talent Peaks High Level Project of Jiangsu Province

项目编号：

62073121U19662022017-XNY-004

出版年：

2024

DOI：

10.17775/CSEEJPES.2020.07030

中国电机工程学会电力与能源系统学报(英文版)

中国电机工程学会

中国电机工程学会电力与能源系统学报(英文版)

CSTPCDEI

ISSN：2096-0042

年,卷(期)：2024.10(4)