Mitigating Space Weather Impacts on the Power Grid in Real-Time: Applying 3-D EarthScope Magnetotelluric Data to Forecasting Reactive Power Loss in Power Transformers

Current efforts to assess risk to the power grid from geomagnetic disturbances (GMDs) that result in geomagnetically induced currents (GICs) seek to identify potential "hotspots," based on statistical models of GMD storm scenarios and power distribution grounding models that assume that the electrical conductivity of the Earth's crust and mantle varies only with depth. The NSF-supported EarthScope Magnetotelluric (MT) Program operated by Oregon State University has mapped 3-D ground electrical conductivity structure across more than half of the continental US. MT data, the naturally occurring time variations in the Earth's vector electric and magnetic fields at ground level, are used to determine the MT impedance tensor for each site (the ratio of horizontal vector electric and magnetic fields at ground level expressed as a complex-valued frequency domain quantity). The impedance provides information on the 3-D electrical conductivity structure of the Earth's crust and mantle. We demonstrate that use of 3-D ground conductivity information significantly improves the fidelity of GIC predictions over existing 1-D approaches. We project real-time magnetic field data streams from US Geological Survey magnetic observatories into a set of linear filters that employ the impedance data and that generate estimates of ground level electric fields at the locations of MT stations. The resulting ground electric fields are projected to and integrated along the path of power transmission lines. This serves as inputs to power flow models that represent the power transmission grid, yielding a time-varying set of quasi-real-time estimates of reactive power loss at the power transformers that are critical infrastructure for power distribution. We demonstrate that peak reactive power loss and hence peak risk for transformer damage from GICs does not necessarily occur during peak GMD storm times, but rather depends on the time-evolution of the polarization of the GMD's inducing fields and the complex ground (3-D) electric field response, and the resulting alignment of the ground electric fields with the power transmission line paths. This is informing our efforts to provide a set of real-time tools for power grid operators to use in mitigating damage from space weather events.