Modelling geomagnetically induced currents in midlatitude Central Europe using a thin-sheet approach

Geomagnetically induced currents (GICs) in power systems, which can lead to transformer damage over the short and the long term, are a result of space weather events and geomagnetic variations. For a long time, only high-latitude areas were considered to be at risk from these currents, but recent studies show that considerable GICs also appear in midlatitude and equatorial countries. In this paper, we present initial results from a GIC model using a thin-sheet approach with detailed surface and subsurface conductivity models to compute the induced geoelectric field. The results are compared to measurements of direct currents in a transformer neutral and show very good agreement for short-period variations such as geomagnetic storms. Long-period signals such as quiet-day diurnal variations are not represented accurately, and we examine the cause of this misfit. The modelling of GICs from regionally varying geoelectric fields is discussed and shown to be an important factor contributing to overall model accuracy. We demonstrate that the Austrian power grid is susceptible to large GICs in the range of tens of amperes, particularly from strong geomagnetic variations in the east–west direction

Restoring efficiency, removing sound

Increased renewable power generation, HVDC interconnections and geomagnetic effects all bias the AC grid with small direct currents which leads to two negative effects on transformers (theory of half-cycle saturation) increased noise and increased no-load losses. A unique solution is the DC compensation system, which is an add-on to a transformer which eliminates the DC effects. Furthermore, there are dedicated steps available, from pure detection of the problem, preparation of the transformer and measurement, all the way up to a full compensation system

Findings on the October Effect

Very Low Frequency (VLF) radio signals provide a unique possibility of continuously monitoring the lower ionosphere and their dynamics since these signals are reflected at the ionospheric D region between 60-90 km. Recent investigations have shown a very sharp decrease in signal amplitude at the beginning of October which deviates from the actual symmetric course of solar zenith angle variation over the year. The effect is developed differently depending on latitude, longitude and frequency, as we will present. In investigation for the cause of this phenomenon, first comparisons suggest a close correlation with the sudden reversal from easterly to westerly zonal flow, the asymmetric peak in semidiurnal solar tide S2, and the progression of the lower mesospheric temperature. Independent of the solar zenith angle mostly in high latitudes, a strong warming of the lower mesosphere during fall can be observed, confirming dominating atmospheric inner dynamics. Further studies are ongoing

Geomagnetically induced current model validation from New Zealand's South Island

Geomagnetically induced currents (GICs) during a space weather event have previously caused transformer damage in New Zealand. During the 2015 St. Patrick's Day Storm, Transpower NZ Ltd has reliable GIC measurements at 23 different transformers across New Zealand's South Island. These observed GICs show large variability, spatially and within a substation. We compare these GICs with those calculated from a modeled geolectric field using a network model of the transmission network with industry‐provided line, earthing, and transformer resistances. We calculate the modeled geoelectric field from the spectra of magnetic field variations interpolated from measurements during this storm and ground conductance using a thin‐sheet model. Modeled and observed GIC spectra are similar, and coherence exceeds the 95% confidence threshold, for most valid frequencies at 18 of the 23 transformers. Sensitivity analysis shows that modeled GICs are most sensitive to variation in magnetic field input, followed by the variation in land conductivity. The assumption that transmission lines follow straight lines or getting the network resistances exactly right is less significant. Comparing modeled and measured GIC time series highlights that this modeling approach is useful for reconstructing the timing, duration, and relative magnitude of GIC peaks during sudden commencement and substorms. However, the model significantly underestimates the magnitude of these peaks, even for a transformer with good spectral match. This is because of the limited range of frequencies for which the thin‐sheet model is valid and severely limits the usefulness of this modeling approach for accurate prediction of peak GICs