The study geomagnetic field variability describing the growth of the GIC in electric power lines

Abstract:

In this study we estimate of the influence of different geomagnetic disturbances (substorms, SC, TCV impulses, Pi3/Pc5 pulsations) on the growth of geomagnetically induced currents (GIC) registered in electric power lines of Kola Peninsula and Karelia (Russia). The continuous registration of GIC in this system is performed since 2010 year. This registration system includes 5 stations elongated in north-south direction. The IMAGE magnetometer data and 2D equivalent currents model was used. The telluric currents are calculated with using crust impedances from the BEAR experiment and IMAGE data.

It is commonly accepted the models in which the auroral electrojet is a main driver of GIC at high latitudes. On the base of this notion it is considered that GIC are dangerous only for the east-west elongated technological lines. However our detail analyses of the GIC, B, dB/dt, E variations shows that small-scale vortex ionosphere currents have a great contribution to rapid GIC growth. The contribution of dY/dt to the GIC growth is comparable and sometimes lager than dX/dt contribution. The rapid jumps of the dB/dt for the time distribution can’t be explained by the slow changing auroral electrojet intensity. So the GIC are dangerous for the technological lines elongated in north-south direction as well.

Contrary to classic point of view it is found that noticeable GIC can better correlate with geomagnetic field variations B than with dB/dt (see Fig.). So the great GIC values may be caused not only by the temporal variations of the geomagnetic field but also by the spatial variation of the vortex-like ionosphere current systems connected with the field-aligned currents in the magnetosphere.

The analysis of the spatial distribution of the geomagnetic field variations and dB/dt shows that its maximums do not coincide in latitude-MLT coordinated. Therefore the maximum amplitude of the geomagnetic field disturbances will not correspond to the maximum of GIC. So the problem of GIC prediction is a wider than AE index prediction.