Data Driven Transfer Functions and Transmission Network Parameters for GIC Modelling

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...

Full description

Saved in:
Bibliographic Details
Published in:arXiv.org 2020-06
Main Authors: Heyns, M J, Gaunt, C T, Lotz, S I, Cilliers, P J
Format: Article
Language:English
Subjects:
Geoelectricity
Geomagnetism
Magnetic storms
Mathematical models
Modelling
Parameter estimation
Parameter identification
Transfer functions
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.2004.08837