Geomagnetically induced currents in Europe

Viljanen, A.; Pirjola, Risto; Prácser, Ernő; Katkalov, Juri; Wik, Magnus

doi:10.1051/swsc/2014006

Cited by 68 publications

(67 citation statements)

References 28 publications

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“…Block numbering refers to Figure 1. Source of the model parameters: http://real.mtak.hu/2957 (available also as supplementary material in Viljanen et al (2014)). Block 48 is relevant only when the Nordic grid model is considered.…”

Section: Resultsmentioning

confidence: 99%

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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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Section: Resultsmentioning

confidence: 99%

“…As the ground conductivity model, we use two cases. One is the EURISGIC model (Adam et al, 2012;Viljanen et al, 2014) in which there are four different 1-D ground structures next to each other in the region considered here (Fig. 1, Table 1).…”

Section: Methodsmentioning

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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“…In addition, the capability for real-time data transmission becomes more and more important, in particular for applications in geohazard monitoring and space weather, e.g. ground-induced currents (Viljanen et al, 2014;Barbosa et al, 2015). Finally, data gaps in operation should be avoided, requiring a system that is easy to operate, safely survives power losses, close-by lightning strikes, and automatically restarts data acquisition as soon as power is available after power loss.…”

Section: Design Criteria and Functionalitymentioning

confidence: 99%

“…Amongst many other examples, geomagnetic observatories are an important source of reliable long-term data to resolve secular variation over several decades to centuries (e.g. Wardinski and Holme, 2006;Jackson et al, 2000), and they are essential to derive indices of geomagnetic activity (e.g. Menvielle et al, 2011) due to their fixed position on Earth.…”

Section: Introductionmentioning

confidence: 99%

A low-power data acquisition system for geomagnetic observatories and variometer stations

Morschhauser

Haseloff

Bronkalla

et al. 2017

Geosci. Instrum. Method. Data Syst.

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Abstract. A modern geomagnetic observatory must provide data of high stability, continuity, and resolution. The INTER-MAGNET network has therefore specified quantitative criteria to ensure a high quality standard of geomagnetic observatories. Here, we present a new data acquisition system which was designed to meet these criteria, in particular with respect to 1 Hz data. This system is based on a Raspberry Pi embedded PC and runs a C++ data acquisition software. As a result, the data acquisition system is modular, cheap, and flexible, and it can be operated in remote areas with limited power supply. In addition, the system is capable of near-realtime data transmission, using a reverse SSH tunnel to work with any network available. The system hardware was successfully tested at the Niemegk observatory for a period of 1 year and subsequently installed at the Tatuoca observatory in Brazil.

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“…In the context of inductionhazard science and the need to develop algorithms for estimating storm-time induction of geoelectric fields, lithospheric conductivity is often modeled as being only depth dependent (e.g., Pulkkinen et al 2007). Recently, however, three-dimensional models have been used in the analysis of storm-time induction (e.g., Püthe and Kuvshinov 2013; Thomson et al 2009;Viljanen et al (2014); in their independent analyses of Kakioka geomagnetic and geoelectric data, Love and Swidinsky Love and Swidinsky (2014) and Püthe et al 2014 each used a time-constant galvanic distortion tensor in their modeling of the polarizing effects of localized three-dimensional lithospheric conductivity. Given our practical goal of obtaining improved estimates of storm-time geoelectric fields, we choose to extend the parameterizations of the preceding analyses in two different ways.…”

Section: Parameterization For 3d Conductivitymentioning

confidence: 99%

Observatory geoelectric fields induced in a two-layer lithosphere during magnetic storms

Love

Swidinsky

2015

Earth Planet Sp

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We report on the development and validation of an algorithm for estimating geoelectric fields induced in the lithosphere beneath an observatory during a magnetic storm. To accommodate induction in three-dimensional lithospheric electrical conductivity, we analyze a simple nine-parameter model: two horizontal layers, each with uniform electrical conductivity properties given by independent distortion tensors. With Laplace transformation of the induction equations into the complex frequency domain, we obtain a transfer function describing induction of observatory geoelectric fields having frequency-dependent polarization. Upon inverse transformation back to the time domain, the convolution of the corresponding impulse-response function with a geomagnetic time series yields an estimated geoelectric time series. We obtain an optimized set of conductivity parameters using 1-s resolution geomagnetic and geoelectric field data collected at the Kakioka, Japan, observatory for five different intense magnetic storms, including the October 2003 Halloween storm; our estimated geoelectric field accounts for 93% of that measured during the Halloween storm. This work demonstrates the need for detailed modeling of the Earth's lithospheric conductivity structure and the utility of co-located geomagnetic and geoelectric monitoring.

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Geomagnetically induced currents in Europe

Abstract: Statistics of geomagnetically induced currents (GIC) in the European high-voltage power grids based on 1-min geomagnetic recordings in 1996-2008 and on

Cited by 68 publications

References 28 publications

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

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

A low-power data acquisition system for geomagnetic observatories and variometer stations

Observatory geoelectric fields induced in a two-layer lithosphere during magnetic storms

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