Geomagnetically induced current model in New Zealand across multiple disturbances: Validation and extension to non‐monitored transformers

Mac Manus, D.H.; Rodger, C.J.; Ingham, M.; Clilverd, M.A. ORCID: https://orcid.org/0000-0002-7388-1529; Dalzell, M.; Divett, T.; Richardson, G.S.; Petersen, T.. 2022 Geomagnetically induced current model in New Zealand across multiple disturbances: Validation and extension to non‐monitored transformers. Space Weather, 20 (2), e2021SW002955. 23, pp. https://doi.org/10.1029/2021SW002955

Before downloading, please read NORA policies.

Preview

Text (Open Access) © 2022. The Authors. Space Weather - 2022 - Mac Manus - Geomagnetically Induced Current Model in New Zealand Across Multiple Disturbances .pdf - Published Version Available under License Creative Commons Attribution 4.0. Download (5MB) | Preview

Abstract/Summary

Geomagnetically induced currents (GICs) produced during geomagnetic disturbances pose a risk to the safe operation of electrical power networks. One route to determine the hazard of large and extreme geomagnetic disturbances to national electrical networks is a validated model to predict GIC across the entire network. In this study we improve upon an earlier model for New Zealand, expanding the approach to cover transformers nationwide by making use of multiple storms to develop national scaling factors. We exploit GIC observations which have been made and archived by Transpower New Zealand Ltd, the national grid operator. For some transformers the GIC observations span nearly 2 decades, while for others only a few years. GICs can vary wildly between transformers, particularly due to differences in the electrical network characteristics , transformer properties, and ground conductivity. Modeling these individual transformers is required if an accurate representation of the GIC distribution throughout the network is to be produced. Here we model the GIC during 25 disturbed periods, ranging from large geomagnetic storms to weakly active periods. We adopt the approach of scaling model output using observed GIC power spectra, finding that it improves the correlations between the maximum model and observed GIC by between 10-40% depending on the transformer. The modeled GIC at the 73 transformers which have measured GIC are analyzed to create local and national scaling curves. These are used to allow modeling for transformers without in-situ GIC. We present approaches to utilise this technique for future storms, including non-monitored transformers.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2021SW002955
ISSN:	1542-7390
Date made live:	09 Feb 2022 13:39 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531916

Actions (login required)

View Item

Document Downloads

More statistics for this item...