<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The methodology for the evaluation of long-term exposure to the overhead line magnetic field is presented, in this paper. The developed methodology is based on the ambient temperature measurements and phase conductors’ height measurements to find a linear regression model to determine phase conductors’ height changes for different ambient temperatures. Based on the overhead transmission line geometry, and datasets about historical overhead line phase current intensity values and ambient temperatures long-term magnetic field exposure can be determined. For magnetic flux density determination, a method based on artificial neural networks is used. The methodology is applied to the case study of overhead line that connect substations Sarajevo 10 and Sarajevo 20. A period of one year is analyzed and magnetic flux density values are determined. The obtained results indicate that during the analyzed period for significant amounts of time magnetic flux density values surpass the recommended values for long-term exposure.</p>
</abstract>

The methodology for the evaluation of long-term exposure to the overhead line magnetic field is presented, in this paper. The developed methodology is based on the ambient temperature measurements and phase conductors’ height measurements to find a linear regression model to determine phase conductors’ height changes for different ambient temperatures. Based on the overhead transmission line geometry, and datasets about historical overhead line phase current intensity values and ambient temperatures long-term magnetic field exposure can be determined. For magnetic flux density determination, a method based on artificial neural networks is used. The methodology is applied to the case study of overhead line that connect substations Sarajevo 10 and Sarajevo 20. A period of one year is analyzed and magnetic flux density values are determined. The obtained results indicate that during the analyzed period for significant amounts of time magnetic flux density values surpass the recommended values for long-term exposure.

Evaluation of the Long-Term Exposure to the Magnetic Fields Generated by Overhead Transmission Lines Using Artificial Neural Networks – A Case Study

Faculty of Electrical Engineering University of Sarajevo

B&H Electrical Engineering

This work is licensed under the Creative Commons Attribution 4.0 International License.

The methodology for the evaluation of long-term exposure to the overhead line magnetic field is presented, in this paper. The developed methodology is based on...

Evaluation of the Long-Term Exposure to the Magnetic Fields Generated by Overhead Transmission Lines Using Artificial Neural Networks – A Case Study

Article Category: Original scientific paper

Online veröffentlicht: 22. Juni 2024

Seitenbereich: 31 - 39

Eingereicht: 20. Mai 2024

Akzeptiert: 04. Juni 2024

DOI: https://doi.org/10.2478/bhee-2024-0004

Schlüsselwörter
magnetic field, long-term exposure, overhead transmission lines, artificial neural networks

© 2024 Ajdin Alihodžić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Evaluation of the Long-Term Exposure to the Magnetic Fields Generated by Overhead Transmission Lines Using Artificial Neural Networks – A Case Study

Article Category: Original scientific paper

Online veröffentlicht: 22. Juni 2024

Seitenbereich: 31 - 39

Eingereicht: 20. Mai 2024

Akzeptiert: 04. Juni 2024

DOI: https://doi.org/10.2478/bhee-2024-0004

Schlüsselwörtermagnetic field, long-term exposure, overhead transmission lines, artificial neural networks

© 2024 Ajdin Alihodžić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
magnetic field, long-term exposure, overhead transmission lines, artificial neural networks