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For the past 18-years Oregon State University and its contractors - under the support of NSF (2006-2018), NASA (2019-2020) and USGS (2020-2024)- installed temporary (weeks-to-months; at 7 Backbone stations - years) long-period MT stations that measure ground-level vector electric and magnetic fields on a 70-km grid of points spanning the conterminous US. A total of 1711 transportable stations whose data meet data quality control standards will have been installed, operated and extracted by mid-2024, completing the MTArray in CONUS. We generate MT Impedance tensors (“EMTF”s, induction vectors and related quantities from the MT time series, suitable for determining the 3-D electrical structure of the crust and upper mantle. The impedances, induction vectors, and/or derived 3-D electrical models can be used to estimate ground-level electric fields from measurements or models of ground-level magnetic fields. These can be integrated along the paths of power grid transmission lines and flowed through power grid equivalent electrical circuits to determine GIC intensity, transformer heat and vibration, and reactive power loss. A look to the future: With a sufficiently dense, real-time telemetering network of MT stations, we have demonstrated how a convolutional neural network trained on measured time series from an array of MT stations may be used to forecast ground-level fields more than 30-minutes in the future, and the potential this has for alerting power utilities of incoming risks to specific HV transformers on the transmission network (reported at this workshop in 2022). 

For the past sixteen years under the support of NSF, NASA and most recently the US Geological Survey, we have been systematically measuring electric and magnetic field time series from moving arrays of magnetotelluric (MT) instrumentation spanning the conterminous US and the interior of Alaska. While originally motivated by questions of the structure and evolution of the North American continent, the resulting 3-D electrical conductivity structure of the Earth's crust and upper mantle and the electromagnetic impedance data derived from this work have in recent years proved of considerable importance to mitigating risk to critical infrastructure (most notably, the power grid) from geomagnetically induced currents caused by space weather and electromagnetic pulse events. Under current NSF support we are exploring how to combine real-time magnetic observatory data streams with this information and with power flow simulations of the power grid to provide real-time alerting information of GIC impacts on high-voltage transformers to electric utilities. In the present work we go beyond real-time and present preliminary results of our efforts to train neural networks to assimilate data from dense arrays of ground-based MT stations in Alaska to provide forecasts of ground electric and magnetic field time series that could in future, with installation of permanent MT arrays, provide actionable intelligence to utilities ahead of GICs impacting their networks. 

Ground-based magnetometers used to measure magnetic fields on the Earth’s surface (B) have played a central role in the development of Heliophysics research for more than a century. These versatile instruments have been adapted to study everything from polar cap dynamics to the equatorial electrojet, from solar wind-magnetosphere-ionosphere coupling to real-time monitoring of space weather impacts on power grids. Due to their low costs and relatively straightforward operational procedures, these instruments have been deployed in large numbers in support of Heliophysics education and citizen science activities. They are also widely used in Heliophysics research internationally and more broadly in the geosciences, lending themselves to international and interdisciplinary collaborations; for example, ground-based electrometers collocated with magnetometers provide important information on the inductive coupling of external magnetic fields to the Earth’s interior through the induced electric field (E). The purpose of this white paper is to (1) summarize present ground-based magnetometer infrastructure, with a focus on US-based activities, (2) summarize research that is needed to improve our understanding of the causes and consequences of B variations, (3) describe the infrastructure and policies needed to support this research and improve space weather models and nowcasts/forecasts. We emphasize a strategic shift to proactively identify operational efficiencies and engage all stakeholders who need B and E to work together to intelligently design new coverage and instrumentation requirements. 

The National Space Weather Action Plan, NERC Reliability Standard TPL-007-1,2 associated FERC Orders 779, 830 and subsequent actions, emerging standard TPL-007-3, as well as Executive Order 13744 have prepared the regulatory framework and roadmap for assessing and mitigating the impact on critical infrastructure from space weather. These actions have resulted in an emerging set of benchmarks against which the statistical probability of damage to critical components such as power transmission system high-voltage transformers can be assessed; for the first time the impacts on the intensity of geomagnetically induced currents (GICs) due to the spatial variability of the geomagnetic field and of the Earth’s electrical conductivity structure can be examined systematically. While at present not a strict requirement of the existing reliability standards, there is growing evidence that the strongly three-dimensional nature of the electrical conductivity structure of the North American crust and mantle (heretofore ‘ground conductivity’) has a first-order impact on GIC intensity, with considerable local and regional variability. The strongly location dependent ground electric field intensification and attenuation due to 3-D ground conductivity variations has an equivalent impact on assessment of risk to critical infrastructure due to HEMP (E3 phase) sources of geomagnetic disturbances (GMDs) as it does for natural GMDs. From 2006-2018, Oregon State University (OSU) under NSF EarthScope Program support, installed and acquired ground electric and magnetic field time series (magnetotelluric, or MT) data on a grid of station locations spaced ~70-km apart, at 1161 long-period MT stations covering nearly ⅔ of CONUS. The US Geological Survey completed 47 additional MT stations using functionally identical instrumentation, and the two data sets were merged and made available in the public domain. OSU and its project collaborators have also collected hundreds of wider frequency bandwidth, more densely-spaced MT station data under other project support, and these have been or will be released for public access in the near future. NSF funding was not available to make possible collection of EarthScope MT data 1/3 of CONUS in the southern tier of states, in a band from central California in the west to Alabama in the east and extending along the Gulf Coast and Deep South. OSU, with NASA support just received, plans to complete MT station installation in the remainder of California this year, and with additional support both anticipated and proposed, we hope to complete the MT array in the remainder of CONUS. For this first time this will provide national-scale 3-D electrical conductivity/MT impedance data throughout the US portion of the contiguous North American power grid. Complementary planning and proposal efforts are underway in Canada, including collaborations between OSU, Athabasca University and other Canadian academic and industry groups. In the present work, we apply algorithms we have developed to make use of real-time streams of US Geological Survey, Natural Resources Canada (and other) magnetic observatory data, and the EarthScope and other MT data sets to provide quasi-real time predictions of the geomagnetically induced voltages at high-voltage transmission system transformers/power buses. This goes beyond the statistical benchmarking process currently encapsulated in NERC reliability standards. We seek initially to provide real-time information to power utility control room operators, in the form of a heat map showing which assets are likely experiencing stress due to induced currents. These assessments will be ground-truthed against transmission system sensor data (PMUs, GIC monitors, voltage waveforms and harmonics where available), and by applying machine learning methods we hope to extend this approach to transmission systems that have sparse or non-existent GIC monitoring sensor infrastructure. Ultimately by incorporating predictive models of the geomagnetic field using satellite data as inputs rather than real-time ground magnetic field measurements, a near-term probabilistic assessment of risk to transformers may be possible, ideally providing at least a 15-minute forecast to utility operators. There has been a concerted effort by NOAA to develop a real-time geomagnetically induced ground electric field data product that makes use of our EarthScope MT data, which includes the strong impacts on GICs due to 3-D ground conductivity structure. Both OSU and the USGS have developed methods to determine the GIC-related voltages at substations by integrating the ground electric fields along power transmission line paths. Under National Science Foundation support, the present team of investigators is taking the next step, of applying the GIC-related voltages as inputs to quasi-real time power flow models of the power transmission grid in order to obtain realistic and verifiable predictions of the intensity of induced GICs, the reactive power loss due to GICs, and of GIC effects on the current and voltage waveforms, such as the harmonic distortion. As we work toward integration of predicted induced substation voltages with power flow models, we’ve modified the RTS-GMLC (Reliability Test System Grid Modernization Lab Consortium) test case (https://github.com/GridMod/RTS-GMLC) by moving the geographic location of the case to central Oregon. With the assistance of LANL we have the complete AC and DC network of the RTS-GMLC case, and we are working to integrate the complete case information into Julia (using the PowerModels and PowerModelsGMD packages of LANL), or into PowerWorld. Along a parallel track, we have performed GIC voltage calculations using our geophysical algorithm for a realistic GMD event (Halloween event) for the test case, resulting in GIC transmission line voltages that can be added into our power system model. We’ll discuss our progress in integrating the geophysical estimates of transformer voltages and our DC model using LANL's Julia and PowerModelsGMD package, for power flow simulations on the test case, and to determine the GIC flows and possible impacts on the power waveforms in the system elements. 

Severe geomagnetic storms can generate significant geo-electric fields that drive damaging quasi-direct currents within electric power grids. In "Space Weather Phase 1 Benchmarks," a report published in June 2018 by the Space Weather Operations, Research, and Mitigation (SWORM) Subcommittee on behalf of the National Science and Technology Council (NSTC), the "Induced Geo-electric Fields" working group (WG) summarized their objectives to: (1) assess the feasibility of establishing functional benchmarks for induced geo-electric fields using currently available storm data sets, existing models, and published literature; and (2) use the existing body of work to produce benchmarks for induced geo-electric fields for specific regions of the United States. To address this, they focused on developing a statistical product that captured maps of geo-electric hazard. Recently, our "next steps" WG reviewed these benchmarks to assess whether they are reasonable, aligned with the stated objectives, and up-to-date, based on new analyses as well as input from the community. We also considered whether the methodology used to derive them should be revised. In this presentation, we summarize the main findings of this WG, including recommendations for future data collection and/or studies that would improve their accuracy and usability, whilst at the same time, reducing the uncertainties associated with them. 

By fusing data obtained from finely spaced continental-scale, magnetotelluric (MT) measurements used for geophysical imaging of the electrical conductivity variations of the Earth's crust and mantle, real-time data of the geomagnetic field variations at a sparse network of fixed geomagnetic observatory and variometer stations, power transmission system sensor data such as neutral ground return current, synchrophasor and other sensor data, information on power grid topology and state, and by applying algorithms we have developed to project the real-time stream of magnetic observatory and variometer data through the frequency-dependent tensor impedances derived from the MT data at each temporary station, we calculate the anomalous voltages on power transmission substations induced by geomagnetically induced currents. Our solution accounts for the first-order impacts on the induced voltages that are due to the effects of 3-D variations in ground (Earth's crust and upper mantle) electrical conductivity structure. These effects when convolved with the path integral of the induced vector ground electric field along the transmission lines are the dominant term in determining the intensity of the geomagnetically induced currents in the system; considerably more so than geomagnetic latitude scaling effects. We discuss integration of real-time geophysical estimates of geomagnetic disturbance induced substation voltages with DC and AC power flow simulations on increasingly realistic models of the topology and state of regional power grids. We are integrating our workflow with the open source PowerModelsGMD.jl power flow simulator developed at Los Alamos National Laboratory, and describe simulations of real-time assessments of stress on critical assets of the power grid including reactive power loss, phase deviations, transformer heating and other metrics of transmission system stress. Such efforts to provide a real-time assessment of risk to critical assets can also inform statistical assessments of system vulnerabilities to "100-yr" or "Carrington" level geomagnetic disturbances. We will discuss how such efforts are informing the development of updated standards that may impact the future regulatory environment that governs efforts to maintain a resilient power transmission system.