Modeling geomagnetic induction hazards using a 3‐D electrical conductivity model of Australia

Wang, Liejun; Lewis, Andrew M.; Ogawa, Yasuo; Jones, William V.; Costelloe, Marina

doi:10.1002/2016sw001436

Cited by 16 publications

(26 citation statements)

References 28 publications

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“…Other than thin-sheet, fully 3-D electric field modeling with plane wave excitation was performed by Beamish et al (2002) for the British Isles region and by Wang et al (2016) for Australia.…”

Section: 1002/2017sw001793mentioning

confidence: 99%

Regional 3‐D Modeling of Ground Electromagnetic Field Due To Realistic Geomagnetic Disturbances

et al. 2018

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During extreme space weather events the fluctuating geomagnetic field induces an electric field in the conducting Earth. This geoelectric field in turn generates currents in ground‐based technological systems, affecting their operation. Thus, calculation of the geoelectric field is a key step in predicting, assessing, and, potentially, forecasting the space weather impact on critical infrastructure. We present an approach and a tool for the first fully coupled regional three‐dimensional (3‐D) forward modeling of the electromagnetic field from far geospace down to the surface of the Earth. Applying the developed tool to the British Isles, we perform a 3‐D study in order to explore in detail the so‐called coastal effect (i.e., the anomalous behavior of the geoelectric field near the coasts) and to understand the limitations of the thin‐sheet model widely used for estimating this effect. For this purpose we compare the results of 3‐D and thin‐sheet modelings for plane wave source of excitation and different periods of variations. We conclude that for the British Isles the thin sheet is a reasonable approximation for periods longer than a few minutes. However, for shorter periods 3‐D modeling is essential. Another inference from the results of 3‐D modeling for plane wave and realistic sources is that for the British Isles the geoelectric field is distorted by the coastal effect practically everywhere on land. Finally, we compare modeled and observed geomagnetic fields at four observatories in the region during the first day of the Halloween storm in 2003 and discuss the results of this comparison.

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Section: 1002/2017sw001793mentioning

confidence: 99%

Regional 3‐D Modeling of Ground Electromagnetic Field Due To Realistic Geomagnetic Disturbances

et al. 2018

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“…The geoelectric field varies rapidly temporarily and spatially as demonstrated, for example, by Beggan et al (2013), Bedrosian and Love (2015), Wei et al (2013) and Wang et al (2016) for regional and continental scales, and by Püthe and Kuvshinov (2013) and Ngwira et al (2015) for global scales. Temporal variations are due to time variations of space currents and are connected with time variations of the geomagnetic field by Faraday's law.…”

Section: Introductionmentioning

confidence: 99%

Influence of spatial variations of the geoelectric field on geomagnetically induced currents

Viljanen

Pirjola

2017

J. Space Weather Space Clim.

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-The geoelectric field driving geomagnetically induced currents (GIC) has complex spatial variations. It follows that different patterns of the field vectors in a given area having the same regional mean can produce very different GIC. In this study, we consider a few power grid models and calculate GIC due to a modelled geoelectric field with a regional mean magnitude of 1 V/km. Altogether 8035 snapshots of the electric field are included. We also assume two different ground conductivity models, of which the simpler one consists of two layers across the whole region, and another model has four different two-layer blocks. As a measure of GIC, we use the sum of currents at all substations of the power grid. We also consider the distribution of GIC at a single site. For a given grid, differences between the two ground conductivity models are small. When comparing different power grid models, the sum of GIC varies relatively more for a grid with a small number of substations and transmission lines. When the area and the number of substations increase, the relative difference between the smallest and largest GIC sum decreases. In all cases, assuming a spatially uniform electric field leads to a reasonable estimation of the GIC magnitudes, but it does not produce the largest GIC sum. For a single substation, there is a large variety of GIC values due to different electric field configurations.

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“…The model is adapted from the layered Earth conductivity model for the north‐west region of Canada as described in Trichtchenko and Boteler (), and readjusted using the Campbell et al () model for Australia. A 1‐D n ‐layer model where conductivity varies in the vertical direction and is different at each geomagnetic field monitoring location over the Australian continent. The conductivity profiles were derived from a conductivity study of the Australian region given in Wang et al () (hereafter referred to as NW). A 3‐D model with conductivity that varies vertically and horizontally which is an extension of the MT tensor analysis described in Wang et al () (hereafter referred to as 3DM).…”

Section: Modelingmentioning

confidence: 99%

“…4. A 3-D model with conductivity that varies vertically and horizontally which is an extension of the MT tensor analysis described in Wang et al (2016) (hereafter referred to as 3DM).…”

Section: Geoelectric Fieldmentioning

confidence: 99%

“…Modeling geoelectric fields at the Earth's surface for GIC studies using finite difference time-dependent solutions to Maxwell's equations for nonuniform source fields has been performed for 2-D (Barnett, 2016) and 3-D (Simpson, 2011) conductivity models of the Earth. A common approach employs a magnetotelluric tensor to describe responses of the Earth's conductivity both vertically and horizontally for a plane wave source (Bedrosian & Love, 2015;Kelbert et al, 2017;Love et al, 2016;Torta et al, 2017;Wang et al, 2016). Although the assumption of the plane wave source might not always be realistic, as discussed in Ivannikova et al (2018), this assumption is reasonable for low-middle latitude regions (Ngwira et al, 2009;Pulkkinen et al, 2005Pulkkinen et al, , 2012Thomson et al, 2005;Viljanen et al, 2006) and is the method used in this paper to incorporate a 3-D conductivity structure into a GIC model for the Australian power network.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Geomagnetically Induced Currents in Australian Power Networks Using Different Conductivity Models

et al. 2019

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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.

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Modeling geomagnetic induction hazards using a 3‐D electrical conductivity model of Australia

Cited by 16 publications

References 28 publications

Regional 3‐D Modeling of Ground Electromagnetic Field Due To Realistic Geomagnetic Disturbances

Regional 3‐D Modeling of Ground Electromagnetic Field Due To Realistic Geomagnetic Disturbances

Influence of spatial variations of the geoelectric field on geomagnetically induced currents

Modeling Geomagnetically Induced Currents in Australian Power Networks Using Different Conductivity Models

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