Analysis of long-term GIC measurements in transformers in Austria

Albert, Dennis A.; Schachinger, Philipp; Bailey, Roger C.; Renner, Herwig; Achleitner, Georg

doi:10.1002/essoar.10508696.1

Cited by 3 publications

(6 citation statements)

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“…Moreover, GICs computations correspond to values mentioned for mid-latitudes by (e.g. Albert et al, 2022;Bailey et al, 2022). For comparison, for Simpevarp-2 power substation on 06 April 2000, Wik et al (2008) reported the highest GIC detected on a power transmission line: 300 A.…”

Section: Gic Analysissupporting

confidence: 76%

“…Moreover, the GIC problems at middle-and low-latitude transmission lines have increasingly gained attention (e.g. Švanda et al, 2021;Bailey et al, 2022;Albert et al, 2022;Tozzi et al, 2019;Zois, 2013;Torta et al, 2012;Barbosa et al, 2015). In the light of this task proposed procedure of the geoelectric field mapping, not based on SECS methods (appropriate for high latitudes) can be tested and applied.…”

Section: Discussionmentioning

confidence: 99%

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Analysis of Large Geomagnetically Induced Currents During the 7-8 September 2017 Storm: Geoelectric Field Mapping

Wawrzaszek¹,

Gil²,

Modzelewska³

et al. 2023

Preprint

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A new 10s resolution GeoElectric Dynamic Mapping (GEDMap) procedure was developed to study Geomagnetically Induced Currents (GICs).• The modeling results performed using the geomagnetic field mapping and Mäntsälä GIC measurements are in excellent agreement. • Rapid and strong evolution of the geoelectric fields occurred at and near Mäntsälä during the two largest GIC events of the magnetic storm.

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Section: Gic Analysissupporting

confidence: 76%

Section: Discussionmentioning

confidence: 99%

Analysis of Large Geomagnetically Induced Currents During the 7-8 September 2017 Storm: Geoelectric Field Mapping

Wawrzaszek¹,

Gil²,

Modzelewska³

et al. 2023

Preprint

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“…If the core material and its hysteresis characteristic is unknown, transformer terminal measurements and the corresponding Ψ– i or Φ– i characteristic can be used to parameterize the transformer hysteresis model. The derived Ψ– i characteristics from a three-phase no-load test have limited value, due to the electromagnetic coupling of the three phases (Albert, 2022; Fuchs and You, 2002). Therefore, different single-phase measurement techniques have been proposed in Fuchs and You (2002) and Albert et al (2021).…”

Section: Hysteresis Measurementmentioning

confidence: 99%

“…For further application also the residual flux inside the transformer core could be of interest, which requires to include a hysteresis model (Martinez and Mork, 2005). Especially, the modelling of the transformer core hysteresis properties, based on terminal measurements, is challenging, due to the magnetic coupling of the phases in multi-winding multi-leg power transformers (Albert, 2022). Different special transformer terminal measurement setups have been discussed to measure the transformer hysteresis characteristic in Neves and Dommel (1995), Fuchs and You(2002) and Albert et al (2021).…”

Section: Introductionmentioning

confidence: 99%

“…The non-linear air gap is based on the assumption that as the step-lap transformer core approaches saturation, the flux is forced also to neighbouring transformer sheets, increasing the flux path through air (see Figure A1). Further information on the air gap modelling can be found in Zirka et al (2022) and Albert (2022). For further application also the residual flux inside the transformer core could be of interest, which requires to include a hysteresis model (Martinez and Mork, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Comparing two topology transformer hysteresis models derived from DC hysteresis measurements

Albert

Domenig

Schachinger

et al. 2023

COMPEL

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Purpose The purpose of this paper is to investigate the applicability of a direct current (DC) hysteresis measurement on power transformer terminals for the subsequent hysteresis model parametrization in transformer grey box topology models. Design/methodology/approach Two transformer topology models with two different hysteresis models are used together with a DC hysteresis measurement via the power transformer terminals to parameterize the hysteresis models by means of an optimization. The calculated current waveform with the derived model in the transformer no-load condition is compared to the measured no-load current waveforms to validate the model. Findings The proposed DC hysteresis measurement via the power transformer terminals is suitable to parametrize two hysteresis models implemented in transformer topology models to calculate the no-load current waveforms. Originality/value Different approaches for the measurement and utilization of transformer terminal measurements for the hysteresis model parametrization are discussed in literature. The transformer topology models, derived with the presented approach, are able to reproduce the transformer no-load current waveform with acceptable accuracy.

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Forecasting GICs and Geoelectric Fields From Solar Wind Data Using LSTMs: Application in Austria

et al. 2022

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The forecasting of local GIC effects has largely relied on the forecasting of dB/dt as a proxy and, to date, little attention has been paid to directly forecasting the geoelectric field or GICs themselves. We approach this problem with machine learning tools, specifically recurrent neural networks or LSTMs by taking solar wind observations as input and training the models to predict two different kinds of output: first, the geoelectric field components Ex and Ey; and second, the GICs in specific substations in Austria. The training is carried out on the geoelectric field and GICs modeled from 26 years of one‐minute geomagnetic field measurements, and results are compared to GIC measurements from recent years. The GICs are generally predicted better by an LSTM trained on values from a specific substation, but only a fraction of the largest GICs are correctly predicted. This model has a correlation with measurements of around 0.6, and a root‐mean‐square error of 0.7 A. The probability of detecting mild activity in GICs is around 50%, and 15% for larger GICs.

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Analysis of long-term GIC measurements in transformers in Austria

Cited by 3 publications

References 0 publications

Analysis of Large Geomagnetically Induced Currents During the 7-8 September 2017 Storm: Geoelectric Field Mapping

Analysis of Large Geomagnetically Induced Currents During the 7-8 September 2017 Storm: Geoelectric Field Mapping

Comparing two topology transformer hysteresis models derived from DC hysteresis measurements

Forecasting GICs and Geoelectric Fields From Solar Wind Data Using LSTMs: Application in Austria

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