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Data Driven Transfer Functions and Transmission Network Parameters for GIC Modelling

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Typical geomagnetically induced current (GIC) modelling assumes the induced quasi-DC current at a node in the transmission network is linearly related to the local geoelectric field by a pair of network parameters. Given a limited time-series of measured geomagnetic and GIC data, an empirical method is presented that results in a statistically significant generalised ensemble of parameter estimates with the error in the estimates identified. The method is showcased for different transmission networks and geomagnetic storms and, where prior modelling exists, shows improved GIC estimation. Furthermore, modelled networks can be locally characterised and probed without any further network knowledge. Insights include network parameter variation, effective network directionality and response. Merging the network parameters and geoelectric field estimation, a transfer function is derived which offers an alternative approach to assessing transformer exposure to GICs.


Michael Heyns    
University of Cape Town / South African National Space Agency
South Africa

Trevor Gaunt    
University of Cape Town
South Africa

Stefan Lotz    
South African National Space Agency
South Africa

Pierre Cilliers    
South African National Space Agency
South Africa


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