A Prediction Model Based on Artificial Neural Network for E1 HEMP Coupling With Distribution Power Lines

Some electromagnetic pulses, such as the high-altitude electromagnetic pulse (HEMP), can couple with power lines in the range of thousands of kilometers. Conventional numerical methods cannot efficiently predict the voltage induced by the early-time (E1) HEMP on the power lines in a large area. This paper presents an efficient model based on an artificial neural network (ANN) which can predict the coupled voltage induced by the E1 HEMP on distribution power lines quickly. Based on Agrawal's model of the electromagnetic field coupling with transmission lines, the important parameters which affect the coupled voltages of distribution power lines are analyzed firstly. The Baum-Liu-Tesche equation and inverse Fourier transform is applied to compute the voltage magnitude when the elevation angle, azimuth angle, and the polarization angle of the E1 HEMP change and more than twenty thousand numerical results are obtained. Then an ANN is developed and trained by the numerical results. Once the ANN is trained, the prediction time is on the order of milliseconds. The results show that the proposed model based on the ANN can provide accurate prediction results for the E1 HEMP coupling with power lines at different observation points.