Modeling Geomagnetically Induced Currents in Australian Power Networks Using Different Conductivity Models. Issue 5 (22nd May 2019)

• Record Type: Journal Article
• Authors: Marshall, R. A.; Wang, L.; Paskos, G. A.; Olivares‐Pulido, G.; Van Der Walt, T.; Ong, C.; Mikkelsen, D.; Hesse, G.; McMahon, B.; Van Wyk, E.; Ivanovich, G.; Spoor, D.; Taylor, C.; Yoshikawa, A.
• Is Part Of: Space weather. Volume 17:Issue 5(2019)
• Page Start: 727
• Page End: 756
• Publication Date: 2019-05-22
• Subjects: modeling GICs -- three‐dimensional conductivity -- magnetotelluric tensors -- power networks -- AusLAMP; Space environment -- Periodicals; 551.509992
• DOI: 10.1029/2018SW002047
• Languages: English
• ISSNs: 1542-7390

Abstract

Abstract: Space weather manifests in power networks as quasi‐DC currents flowing in and out of the power system through the grounded neutrals of high‐voltage transformers, referred to as geomagnetically induced currents. This paper presents a comparison of modeled geomagnetically induced currents, determined using geoelectric fields derived from four different impedance models employing different conductivity structures, with geomagnetically induced current measurements from within the power system of the eastern states of Australia. The four different impedance models are a uniform conductivity model (UC), one‐dimensional n ‐layered conductivity models (NU and NW), and a three‐dimensional conductivity model of the Australian region (3DM) from which magnetotelluric impedance tensors are calculated. The modeled 3DM tensors show good agreement with measured magnetotelluric tensors obtained from recently released data from the Australian Lithospheric Architecture Magnetotelluric Project. The four different impedance models are applied to a network model for four geomagnetic storms of solar cycle 24 and compared with observations from up to eight different locations within the network. The models are assessed using several statistical performance parameters. For correlation values greater than 0.8 and amplitude scale factors less than 2, the 3DM model performs better than the simpler conductivity models. When considering the model performance parameter, P, the highest individual P value was for the 3DM model. The implications of the results are discussed in terms of the underlying geological structures and the power network electrical parameters. Key Points: The study aims to understand the influence of Australia's underlying geology when modeling GICs in Australian power networks The study compares modeled and measured GICs to assess the influence of different conductivity structures