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During geomagnetic storms the electrical power grid is vulnerable to geomagnetically induced currents (GICs) caused by sharp changes in magnetic and geoelectric fields. In the UK the measurement of GIC in the power grid is extremely limited with most GIC estimates coming from a model of the high voltage grid. The US has collected geomagnetic disturbance (GMD) data for 18 geomagnetic storms. Network theory is routinely used to estimate the resilience of the physical power grid, and its robustness to the removal of nodes, when faced with threats ranging from natural hazards to cyber-attacks but is currently not applied to GIC. By applying network theory to both the modelled UK dataset and measured US dataset, we can utilize known parameters to test for vulnerabilities to space weather in the power grid across varying spatial and temporal scales. The network is formed using methods of association between the GIC data at each transformer. The monitors are the nodes of the network and the links are defined as when the wavelet cross-correlation of the GIC is sufficiently high (1). The wavelet transform is used to localise the GIC response to the storm across time scales. Whilst previous network science studies have focused on the physical topology of the power grid, our method focuses on the dynamical response of the grid to GIC. Despite the difference in latitude and local time we see many similarities between the modelled UK and measured US GIC data, particularly during the sudden commencement. Initial results show the same nodes repeatedly appearing as the most highly connected to the network across multiple events. These nodes could be key to providing resilience and/or prediction of forthcoming disturbance of the power grid in the event of a large geomagnetic storm. (1) Orr, L., Chapman, S. C., Beggan, C. D. (2021). Space Weather, 19, e2021SW002772.
Orr et al. (Fri,) studied this question.