STUDY OF INFLUENCE OF HIGHER HARMONICS ON RELIABILITY CABLE NETWORKS

Abstract

This study is devoted to the analysis of the cable network of industrial enterprises with a significant number of cable lines with a voltage of 10 kV. A feature of this electric power supply unit is a powerful direct current valve electric drive for rolling production. The schematic diagram of the cable network is shown in the figure, the total length of the cables is more than 20 km. The results of previous experimental studies made it possible to determine the magnitude and spectrum of harmonics in this node, namely: in 5 harmonics do not exceed 1.5%, but abnormal n = 22—40 determine the value of the non-sinusoidal voltage coefficient within the limits of 5.5—8.9%, which exceeds the 5% norm. The plans of the conducted research also included the measurement of single-phase ground fault currents, which gave the following results for workshop substations: PS-4 — 24.2 A; PS-5 — 17.3 A; PS-5 — 14.8 A. Analyzing the problem of the reliability of cable networks, it is necessary to take into account one more indicator — the value of the leakage currents. A significant number of high-voltage cables are insulated with cable paper impregnated with oil-rosin mastic. Such insulation contains gas inclusions that, under the influence of high-frequency electric shocks, are ionized with subsequent neutralization, which leads to its local damage. Oscillograms of the supply voltage show a sharp shape of the curve as a result of the presence of higher harmonics, which causes the aging of the insulation due to the acceleration of physicochemical processes in the dielectric. Thus, the results of theoretical and experimental studies made it possible to substantiate the main factors that determine the operational reliability of cables, namely: the dynamics of leakage currents, the value of the coefficient of non-sinusoidal voltage caused by abnormal harmonics. Analysis of the specified characteristics allows you to assess the current state of the cable network and predict the reliability of work in the future.