Selection of Measurements in Topology Estimation with Mutual Information

被引：0

作者：

Krstulovic, Jakov ^{[1
]}

Miranda, Vladimiro ^{[1
]}

机构：

[1] INESC TEC Porto, Oporto, Portugal

来源：

2014 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON 2014) | 2014年

关键词：

Mutual information; autoencoders; feature selection; power system topology estimation; STATE ESTIMATION; IDENTIFICATION; ERRORS;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper discusses mechanisms for establishing an efficient decentralized methodology for the reconstruction of topology in power systems. The maximum mutual information criterion is proposed as a selection criterion for the inputs of a distributed topology estimator, based on mosaic of local auto-associative neural networks. The proposed concepts offer some strong theoretical support for an information theoretic perspective on power system state estimation. The results are confirmed by extensive tests conducted on the IEEE RTS 24-bus system.

引用

页码：589 / 596

页数：8

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