Monitoring and Classification of Nonlinear Loads based on Artificial Neural Networks

被引：0

作者：

Stosovic, Miona Andrejevic ^{[1
]}

Stevanovic, Dejan ^{[2
]}

Dimitrijevic, Marko ^{[1
]}

机构：

[1] Univ Nis, Fac Elect Engn, Aleksandra Medvedeva 14, Nish 18000, Serbia

[2] ICAT, Bulevar Nikole Tesle 16, Nish 18000, Serbia

来源：

2017 13TH INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES, SYSTEMS AND SERVICES IN TELECOMMUNICATIONS (TELSIKS) | 2017年

关键词：

Artificial neural networks; Distortion power; Load monitoring;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper artificial neural networks are used for identification of nonlinear loads on the network, as one of the methods for non-intrusive load monitoring. Specific parameters of a group of the nonlinear loads are first measured, and then a neural network is used in order to identify which load, or group of loads, is active on the network. It is shown within an example that the task of loads identification can be done successfully.

引用

页码：443 / 446

页数：4

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