Machine Learning Model for Electric and Magnetic Fields Estimation in the Proximity of Overhead Transmission Lines

被引：2

作者：

Alihodzic, Ajdin ^{[1
]}

Turajlic, Emir ^{[1
]}

Mujezinovic, Adnan ^{[1
]}

机构：

[1] Univ Sarajevo, Fac Elect Engn, Sarajevo, Bosnia & Herceg

来源：

2021 29TH TELECOMMUNICATIONS FORUM (TELFOR) | 2021年

关键词：

Artificial neural networks; electric field intensity; magnetic flux density; overhead transmission lines; POWER-LINES;

D O I：

10.1109/TELFOR52709.2021.9653359

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper considers the application of machine learning models to electric field intensity and magnetic flux density estimation in the proximity of the overhead transmission lines. The machine learning models are applied on two horizontal overhead transmission line configurations at different rated voltages, at height 1 m above ground surface. The obtained results are compared with the results obtained by charge simulation method and Biot-Savart law based method as well as with the field measurement results.

引用

页数：4

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