Estimation of the Spatial and Temporal Distribution of Magnetic Fields around Overhead Power Lines—A Case Study

Ionel Pavel, Camelia Petrescu (), Valeriu David and Eduard Lunca
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Ionel Pavel: Faculty of Electrical Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania
Camelia Petrescu: Faculty of Electrical Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania
Valeriu David: Faculty of Electrical Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania
Eduard Lunca: Faculty of Electrical Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania

Mathematics, 2023, vol. 11, issue 10, 1-15

Abstract: Due to the growing number, diversity and spreading of magnetic field sources, an increasing need to determine the field levels of human exposure has arisen. Some of the most encountered sources are the overhead power lines (OPL) and the determination of spatial and temporal variation of the magnetic fields produced by OPLs is a challenge. In this paper a hybrid method for the estimation of the temporal and spatial distribution of the magnetic flux density B caused by OPLs, based on experimental measurements and on numerical and analytical simulations, is presented. Thus, using a small number of simultaneous spot measurements correlated with a long-term survey, maps of the magnetic flux density distribution on extended areas are established, for several time instances. The proposed method is verified using two sets of different measurements and the results obtained through simulation. The difference between the estimated and simulated values of B is under 5.5%, which is considered acceptable considering that B spans over a large set of values (724 nT ÷ 1375 nT) in the location of the long-term survey procedure. The possibilities and limitations of the proposed method are discussed.

Keywords: magnetic field survey; experimental determination of magnetic fields; modeling and simulation of OPLs (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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