Electric and Magnetic Fields Estimation for Live Transmission Line Right of Way Workers Using Artificial Neural Network

This paper presents an estimation study for live transmission line workers exposed to power frequency electric and magnetic fields using a generalized regression neural network (GRNN). A real double circuit transmission line is selected. The live-line worker is exposed to fields in the right of way of the transmission at 3.28 feet (1 m) above the ground. Both fields´ associated values have been generated using EPRI´s EMF workstation software. The calculations are based on the charge simulation method for the electric field, and Biot-Savart law for the magnetic field. The generalization capability of the designed GRNN network under large number of worker positions within the right of way has been tested and predicted. Fast performance, accurate evaluation, and very good prediction have been obtained for the testing that covers the whole area.