PFI:BIC - A Smart GIC-Resilient Power Grid: Cognitive Control Enabled by Data Mining at the Nexus of Space Weather, Geophysics and Power Systems Engineering

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The North American power grid is potentially at risk of collapse from large geomagnetic storms manifested from solar flares that generate geomagnetically induced currents (GICs) to flow in the power grid. In 2008, with the signing of the American Recovery Act, a $328M investment was made for the installation of high speed sensors called synchrophasors. These generalized power sensors provided, for the very first time, a system potentially capable of wide area situational awareness for the grid. By developing algorithms that interrogate these existing sensor arrays, combining them with real-time predictions of GICs in the power grid determined from real-time geomagnetic field data that is input to information on 3-D ground (crust and mantle) electrical conductivity structure obtained from the NSF EarthScope Magnetotelluric Program, a "Smart Service System" will be developed that will be capable of predicting impact severity on individual power grid transformers. This project will provide an important new tool for mitigating the impact of GICs on the power grid, improving the reliability of electric power service, potentially reducing the possibility of catastrophic blackouts, and reducing costs to power utilities and consumers by extending the service life of key components of the grid.The NSF EarthScope Magnetotelluric Program has systematically measured the electromagnetic impedance of the ground at a temporary grid of stations that currently encompasses more than half of the continental US. The impedance, a frequency dependent tensor sensitive to the 3-D electrical conductivity structure of the Earth?s crust and mantle projects the ground magnetic fields into electric fields at that location. We will apply real-time streams of data from magnetic observatories to determine real-time magnetic fields at the sites of previously occupied EarthScope stations, and by projecting these through the impedance tensors and interpolating the predicted ground electric fields onto power transmission line paths, voltages that drive GICs in power grid transformers can be estimated in real-time and used as input to improved grid power flow simulations that will be developed under project support. This will be integrated with power flow information from mining synchrophasor sensor networks, and with satellite space weather data and NOAA geomagnetic activity forecasts. Human factors engineering will study power utility control room operator interactions with the data flow and user interface developed under project support, with iterative improvements of those interfaces made, given human factors feedback.