Presentation description

Geomagnetically induced currents (GICs) are electric currents generated in power grids during space weather events, such as solar storms. When charged particles ejected by the Sun reach Earth, they can travel along magnetic field lines and cause changes in the geomagnetic field. This ultimately creates voltage gradients at the Earth's surface that drive unwanted currents through grounded conductors like power transmission lines. Since GICs are quasi-direct current (DC), they can flow through high-voltage transformers and other grid infrastructure not designed to handle them. The resulting effects can include transformer overheating, an increase in unwanted reactive power, and in extreme cases, large-scale power outages like the 1989 Hydro-Québec blackout.

Previous research on GICs has primarily focused on simplified models using quasi-static assumptions and 1-D Earth conductivity profiles to estimate surface electric fields. These models have provided valuable insights into GIC behavior during geomagnetic storms but often fail to capture localized variations due to complex geological structures or dynamic space weather conditions. More recent efforts have incorporated magnetotelluric survey data and real-time geomagnetic measurements, improving regional accuracy. Grid-based, time-dependent electromagnetic simulations that can account for 3-D lithosphere compositions and arbitrary ionosphere current behavior have still not been widely adopted by the GIC community. Further, no methodology currently exists to solve for GICs directly from ionospheric currents in a single simulation.

Our research is focused on predicting GICs using Maxwell's equations finite-difference time-domain (FDTD) models that simultaneously account for disturbed ionosphere currents, 3-D lithosphere compositions, and actual power line geometries. Working towards this goal, we incorporate and test in a 2-D FDTD model a thin-wire algorithm that represents a power line. Our goal is to help power utilities prepare for GIC events and improve grid resilience.