Geomagnetically Induced Currents Data Research Articles

Revealing Novel Connections Between Space Weather and the Power Grid: Network Analysis of Ground‐Based Magnetometer and Geomagnetically Induced Currents (GIC) Measurements

AbstractThe growing depth and breadth of data spanning the solar‐terrestrial environment requires new ways of representing and analyzing the available information. This paper applies one such new data representation—network analysis—to the study of Geomagnetically Induced Currents (GICs) in electric power lines. This work uses newly available electric current data collected by power utilities through the the Electric Power Research Institute (EPRI) SUNBURST project and magnetometer data from the Super Magnetometer Initiative. The magnetometer data are analyzed using wavelet analysis. This new analysis method shows deviations to be more likely for equatorial stations close to water, which may be caused by the coast effect. The deviation likelihood is a complex function of latitude and magnetic local time. The GIC data are analyzed using “Quiet Day Curves” (QDCs) which help isolate geomagnetic disturbances. We find that current deviations are more common in the early morning sector, but this trend differs from station to station. These current and magnetometer data are represented in a network as nodes which are connected when both the current and magnetic measurements have a statistically significant deviation from their baseline behavior. This network is used to study the link between space weather and GICs. To do this, times when a current deviation exists are compared to times when magnetic deviations exist for each magnetometer ‐ current sensor pair. Current deviations are, on average, 1.83 times more likely when there are magnetic deviations. However, some magnetometer deviations are more indicative than others, with the strongest probability multipliers reaching 3.

Geomagnetically Induced Currents: Frequency Spectra and Threats to Voltage Stability

Geomagnetically Induced Currents (GICs) are induced after a complex interaction between the sun and earth’s magnetic field. GICs may cripple power systems leading to voltage collapse and a drop in power quality. While the commonly-used dc model for GICs is valid for steady-state analyses of power systems and transformer responses, GICs must be represented with their continuously varying magnitudes and frequency components to understand the dynamic power system’s response to solar storms. In this paper, we used measured GIC data from the 2003 Halloween storm to compare several signal processing techniques. The Fast Fourier Transform (FFT) with a fixed window size, Short-Time Fourier Transform (STFT) with a variable window size, wavelet transform, and Particle-Swarm Optimization (PSO) methods were used to identify the GIC frequency characteristics. To understand the effects of these GIC characteristics on voltage stability, a multi-machine network was modelled on a digital real-time simulator (OPAL-RT). The results reveal the limitations of fixed window FFT in capturing the dominant high-frequency GIC bandwidth arising during peak solar activity. Wavelet and STFT are recommended for GIC data analysis as they provide time-frequency localization. High-frequency GICs during sudden storm commencements and pulsation activity are more of a concern for voltage stability than lower frequency components. Novel results from this study suggest that limiting contingency analysis to only high magnitudes of dc/GIC does not cater for the underlining GIC dynamics. In addition to magnitude thresholds, contingency analysis should incorporate GIC characteristics such as frequency which affect voltage dynamics and thus power system stability.

New Detailed Modeling of GICs in the Spanish Power Transmission Grid

AbstractThe threat of Geomagnetically Induced Currents (GICs) driven by severe Space Weather looms over technological systems such as power grids. Assessing their vulnerability is thus vital to avoid damages or even disruption of the electrical power supply. This endeavor, however, entails an interdisciplinary approach, ranging from the characterization of the geoelectrical structure of the Earth beneath and around the area of interest, or the modeling of the power network from its parameters and topology, and including the validation of the modeling process by means of (direct or indirect) GIC flow measurements. In this paper, we summarize our current achievements focused on mainland Spain, concentrating on the improvements reached after going from a homogeneous Earth's resistivity to an alternative 3D electrical resistivity distribution approach to geoelectric field computation, which is still in progress because new empirical impedance tensors are needed, mainly at sites in the west of the Iberian Peninsula. The second major achievement has come from the addition of the 220 kV level to the network model. The overall improvement has been validated against real GIC data in one area of the country. The new vulnerability maps show that in some nodes the predicted GIC has been substantially reduced by the sum of both effects. The assessment has been carried out down to the level of the individual windings of each transformer, and examples of the estimated GIC flow are given for substations with numerous power transmission lines converging to them at diverse orientations.

Comparison of Deep Learning Techniques to Model Connections Between Solar Wind and Ground Magnetic Perturbations

Geomagnetically induced currents (GIC) can drive power outages and damage power grid components while also affecting pipelines and train systems. Developing the ability to predict local GICs is important to protecting infrastructure and limiting the impact of geomagnetic storms on public safety and the economy. While GIC data is not readily available, variations in the magnetic field, dB=dt, measured by ground magnetometers can be used as a proxy for GICs.We are developing a set of neural networks to predict the horizontal component of the magnetic field, BH, from which dBH=dt is calculated. We apply two techniques for time series analysis to study the connection of solar wind and interplanetary magnetic field properties obtained from the OMNI dataset to the ground magnetic field perturbations. The analysis techniques include a feed-forward artificial neural network (ANN) and a long-short term memory (LSTM) neural network. Here we present a comparison of both models performance when predicting the BH component of the Ottawa (OTT) ground magnetometer for the year 2011 and 2015 and then when attempting to reconstruct the time series of BH for two geomagnetic storms that occurred on 5 August 2011 and 17 March 2015.

HILDCAA‐Related GIC and Possible Corrosion Hazard in Underground Pipelines: A Comparison Based on Wavelet Transform

AbstractHigh‐intensity long‐duration continuous auroral electrojet activities (HILDCAAs) are recognized as the continuous (duration >2 days) auroral electrojet activities (AE > 1,000 nT) caused by interplanetary Alfvén waves driving magnetic reconnection at the Earth's magnetopause. This paper focuses on the study of geoeffectiveness of HILDCAA on the basis of associated geomagnetically induced currents (GICs) and pipe‐to‐soil voltage (PSV) observed in an underground pipeline at Finnish Natural Gas Station, Mäntsälä. In this study, 113 HILDCAAs with different interplanetary sources (72 corotating interaction region‐storm preceded, 29 interplanetary coronal mass ejection‐storm preceded, and 12 nonstorm) have been selected and their possible contributions in underground pipeline corrosion have been quantitatively compared by assessing GIC/PSV profiles for each of these events. In addition, the spectral characteristics of GIC during these events have been studied using continuous wavelet transforms. The Morlet wavelet has been applied to 10‐s modeled GIC data corresponding to each event to explore the main band structures and the periodicities found in GIC spectrum. GIC/PSV modeling is based on plane wave method and distributed source transmission line analogy between pipelines and electric circuits. HILDCAAs are found to drive a small‐amplitude, but continuous, fluctuation in GIC throughout the event duration of several days. This makes the cumulative effect of HILDCAAs in pipeline corrosion noteworthy. The spectral analysis shows that GIC possesses both short‐term, as well as continuous, power distribution with different periodicities. CIR‐preceded HILDCAAs are found to be more geoeffective while taking associated GIC and PSV into account. Possible physical explanations supporting the results have been presented.

The Effect of Tidal Geoelectric Fields on GIC and PSP in Buried Pipelines

Compared with the investigation of geomagnetically induced currents (GIC) in power grids, there is less study about the effect of geomagnetic disturbance (GMD) on buried oil and gas pipelines in mid-low latitude areas, which includes GIC and pipe-to-soil potentials (PSP) effects. Therefore, it is of great significance to research the GMD effect in the mid-low latitudes. For this purpose, we performed the observation experiments on GMD influencing the GIC and PSP in China’s oil and gas pipelines. The data of GIC and PSP in the pipelines are obtained, which do not pertain to the characteristics of the geomagnetic storms caused by solar activity, as well as the GIC and PSP monitoring data deriving from geomagnetic storm on May 21, 2016. By analyzing the characteristics of waveform, frequency and phase of the geoelectric fields data from Lingyang Geomagnetic Observatory ( $35^{\circ } 32^\prime \text{N}$ , $118^{\circ } 52^\prime \text{E}$ ) 60 km away in northeast from the pipeline observation site, the study corroborated that GIC and PSP variations are driven by tidal geoelectric fields (TGF) during the geomagnetic quiet days in this paper. The mechanism of GIC generated by tidal geoelectric field is analyzed. Likewise, an analysis of GMD data from the Maling Mountain Geomagnetic Observatory ( $34^{\circ } 42^\prime \text{N}$ , $118^{\circ } 27^\prime \text{E}$ ), the GIC and the PSP have been done, it is illustrated that the GIC and PSP effects are caused by TGF and geomagnetic storm induced geoelectric field together during a geomagnetic storm. The results demonstrated that, near large areas of water, the effect of tidal geoelectric field on pipeline corrosion is persistent and serious. TGF impacts the calculation accuracy of GIC in pipelines and PSP. Therefore, we should account for the errors caused by TGF when calculating GIC and PSP in pipelines near seashores and a large body of water.

Transmission System Geomagnetically Induced Current Model Validation

Geomagnetically induced currents (GICs) have the potential to severely disrupt power system operations by causing increased reactive power losses in the high-voltage transmission grid. This paper focuses on validating the model which relates the GICs to their deriving electric field. A novel validation framework is proposed with the advantage of considering the system uncertainties and network information availability. The effectiveness of this approaches is validated using both a 20 bus test system as well as actual GIC data provided by American Transmission Company.

Calculation of geomagnetically induced currents reactive power loss disturbance in China’s UHV power grid considering the influence of 500 kV power grid

Geomagnetically induced currents (GIC) in power systems which are generated during magnetic storms, increased reactive power consumption in transformers, it is necessary for geomagnetic storms disaster prevention in power system to calculate GIC-Q increment and recognize voltage changes of substation nodes under simultaneity and proruption of massive GIC-Q loss disturbance in whole power grid. A method combines U - I curve and transformers’ reactive loss coefficient parameter K is proposed to calculate transformers’ GIC-Q increment, based on the GIC data of 1000 kV UHV power network in China, and considering the influence of 500 kV transformers’ GIC-Q loss on 1000 kV power grid, we used the Newton method to calculate voltage fluctuation of 1000 and 500 kV power grid under GIC-Q disturbance. At last, the impact of the simultaneity of massive GIC-Q loss on the 1000 and 500 kV grid is analyzed, we investigated the mutual influence between these two power grids under all circumstances. The results show that 1000 kV Fuzhou substation has a maximum voltage fluctuation that drops by 74.48 kV, whose voltage deviation compared with normal shows a decrease of 7.13%, which beyonds the regulation that the operating voltage deviation should not exceed ±5%. And whether the suddenly voltage drop of 74.48 kV can lead to the reduction of SVC devices reactive power output, and the simultaneity of massive GIC-Q loss as well as the suddenly reduction effect of SVC reactive power output need to be further researched.

Installation of Induced Current Measurement Systems in Substations and Analysis of GIC Data during Geomagnetic Storms

Coronal Mass Ejections (CME), which originate from active regions of the Sun`s surface, e.g., sunspots, result in geomagnetic storms on Earth. The variation of the Earth`s geomagnetic field during such storms induces surface currents that could cause breakdowns in electricity power grids. Hence, it is essential to both monitor Geomagnetically Induced Currents (GICs) in real time and analyze previous GIC data. In 2012, in order to monitor the variation of GICs, the Korean Space Weather Center (KSWC) installed an induced current measurement system at SINGAPYEONG Substation, which is equipped with 765 kV extra-high-voltage transformers. Furthermore, in 2014, two induced current measurement systems were installed on the 345 kV high-voltage transformers at the MIGEUM and SINPOCHEON substations. This paper reports the installation process of the induced current measurement systems at these three substations. Furthermore, it presents the results of both an analysis performed using GIC data measured at the SINGAPYEONG Substation during periods of geomagnetic storms from July 2013 through April 2015 and the comparison between the obtained GIC data and magnetic field variation (dH/dt) data measured at the Icheon geomagnetic observatory.

Impact of the EHV Power System on Geomagnetically Induced Currents in the UHV Power System

Earlier calculations of geomagnetically induced currents (GICs) in Chinese power grids have mainly concentrated on the highest voltage-level system whose geomagnetic risk is considered to be the largest, thus ignoring secondary voltage-level systems. With the 1000-kV system being newly added to China's power system, it is significant to figure out the interaction between GIC in the 500 kV [extremely high voltage (EHV)] system and GIC in the 1000 kV [ultra-high voltage (UHV)] system. Based on the North China-Central China-East China Power Grids, this paper establishes a single-voltage grid by only considering the 1000-kV system and a dual-voltage grid by considering the 1000- and 500-kV systems and investigates GIC in these two grids by developing their GIC “Full-node models.” The impact of the 500-kV system on GIC in the 1000-kV system is analyzed. GIC risks in the UHV and EHV systems are assessed by comparing calculated GIC data with monitored values of GIC. The results show that the impact of the 500-kV system on GIC in the 1000-kV system is obvious, both the EHV and the UHV grid have a high GIC risk. So calculating GIC in the UHV system and in the EHV system should utilize GIC modeling methods for multivoltage power grids.

Estimation of geomagnetically induced currents based on the measurement data of a transformer in a Japanese power network and geoelectric field observations

Geomagnetically induced currents (GICs) have the potential to cause electric power blackouts. Hence, it is important to study the effects of GICs produced by intense geomagnetic storms. The measurements of GICs were conducted at the Memanbetsu substation, Hokkaido, between December 2005 and March 2008. We obtain the complementary cumulative distribution function (CCDF) of the measured GICs and the empirical equation to estimate GICs using the GIC data and geoelectric field observation data. GICs associated with the past intense geomagnetic storms, e.g., the March 13–15 storm and the October 29–30, 2003 storm, are estimated.

Analysis of geomagnetically induced currents at a low-latitude region over the solar cycles 23 and 24: comparison between measurements and calculations

Geomagnetically Induced Currents (GIC) are a space weather effect, which affects ground-based technological structures at all latitudes on the Earth’s surface. GIC occurrence and amplitudes have been monitored in power grids located at high and middle latitudes since 1970s and 1980s, respectively. This monitoring provides information about the GIC intensity and the frequency of occurrence during geomagnetic storms. In this paper, we investigate GIC occurrence in a power network at low latitudes (in the central Brazilian region) during the solar cycles 23 and 24. Calculated and measured GIC data are compared for the most intense geomagnetic storms (i.e. −50 < Dst < −50 nT) of the solar cycle 24. The results obtained from this comparison show a good agreement. The success of the model employed for the calculation of GIC leads to the possibility of determining GIC for events during the solar cycle 23 as well. Calculated GIC in one transformer reached ca. 30 A during the “Halloween storm” in 2003 whilst most frequent intensities lie below 10 A. The normalized inverse cumulative frequency for GIC data was calculated for the solar cycle 23 in order to perform a statistical analysis. It was found that a q-exponential Tsallis distribution fits the calculated GIC frequency distribution for more than 99% of the data. This analysis provides an overview of the long-term GIC monitoring at low latitudes and suggests new insight into critical phenomena involved in the GIC generation.

Observations and modeling of GIC in the Chinese large-scale high-voltage power networks

During geomagnetic storms, the geomagnetically induced currents (GIC) cause bias fluxes in transformers, resulting in half-cycle saturation. Severely distorted exciting currents, which contain significant amounts of harmonics, threaten the safe operation of equipment and even the whole power system. In this paper, we compare GIC data measured in transformer neutrals and magnetic recordings in China, and show that the GIC amplitudes can be quite large even in mid-low latitude areas. The GIC in the Chinese Northwest 750 kV Power Grid are modeled based on the plane wave assumption. The results show that GIC flowing in some transformers exceed 30 A/phase during strong geomagnetic storms. GIC are thus not only a high-latitude problem but networks in middle and low latitudes can be impacted as well, which needs careful attention.

Geomagnetically Induced Currents in the High-Voltage Power Grid in China

With the operation of long transmission lines, unknown severe vibration and noise in transformers have sometimes been observed at the Shanghe substation and at the Ling'ao nuclear power plant in China. This paper gives a comparison of magnetic-storm recordings and measured transformer neutral current data and confirms that the disturbances were caused by geomagnetically induced currents (GICs). On November 7 and 9, 2004, the maximum GIC at the Ling'ao nuclear power plant was 47.2 A and 75.5 A, respectively, which are both larger than the neutral DC current caused by the HVDC monopole operation. The analysis of GIC data indicates that the GIC level is mainly determined by the geomagnetic-field variation rate, but the earth conductivity and power grid parameters are also important factors affecting GIC values. The data show that the GIC level is higher at the Ling'ao nuclear power plant than at the Shanghe substation. The reason is considered to be related to the grid structure and to the coast effect. Furthermore, because of smaller resistances, longer transmission lines, a larger scale, and the adoption of single-phase transformers, the influences of GIC on the ultra-high voltage power grid being constructed in China need to be studied more urgently.

Improved modeling of geomagnetically induced currents in the South African power network

Geomagnetically induced currents (GICs), resulting from adverse space weather, have been demonstrated to cause damage to power transformers in the midlatitudes. There is growing concern over possible GIC effects in the Southern African network because of its long power lines. Previous efforts to model the electric field associated with GICs in South Africa have used a uniform ground conductivity model. In an effort to improve the modeling of GICs, GIC data together with the Hermanus Magnetic Observatory geomagnetic field data were used in order to obtain a multilayered ground conductivity structure. The method requires a definition of the network coefficients, which are then used in subsequent calculations. This study shows that GIC computed using the new network coefficients and the multilayered ground conductivity model improves the accuracy of GIC modeling. GIC statistics are then derived on the basis of the recordings of the geomagnetic field from 1996 to 2006 at Hermanus, the new network coefficients, and ground conductivity model. The geoelectric field was modeled using the plane wave method.

Recordings of geomagnetically induced currents and a nowcasting service of the Finnish natural gas pipeline system

The geomagnetically induced currents (GIC) in the Finnish natural gas pipeline have been measured at one site in southern Finland since November 1998. We give an overview of this long and uniform time series covering one sunspot maximum. We also briefly discuss the conventional magnetic activity indices K and Ak, and, additionally, the range of the magnetic field and of its time derivative, as indicators of the GIC activity. The measured GIC data formed the basis of the development of a nowcasting service (GIC Now!), which was implemented within the European Space Agency Space Weather Applications Pilot Project. The service provides a near‐real‐time view of the geomagnetic activity level and nowcast estimates of GIC and pipe‐to‐soil voltages in the Finnish natural gas pipeline system. We describe the operation and validation of this service in this paper.

Modeling Geomagnetically Induced Currents Using Geomagnetic Indices and Data

The possibilities of forecasting geomagnetically induced currents (GIC) in power transmission networks are dependent on the success in modeling these currents. To provide a valuable user-oriented forecast, modeling and proper evaluation of the models using GIC data is important. Many forecasts of geomagnetic storms are presented in terms of geomagnetic indices. Using the GIC data from measuring sites on three power systems in aurora and subauroral regions we estimate the correlation of 3-hourly peak GIC with global geomagnetic indices (3-h ap) and 1 h peak GIC with hourly magnetic range and peak dB/dt values. Geomagnetic 1-min data were used with physics-based and empirical models of the earth and power system response to calculate GIC. These calculated GIC were tested by determining the correlation with measured GIC. Our results show that local geomagnetic indices are better correlated with peak GIC values than are global indices in describing GIC. Correlation coefficients for local (global) indices are 0.9 (0.8) for two subauroral sites and 0.8 (0.7) for an auroral site. Tests of the correlation between 1 min dB/dt or calculated electric field values with measured GIC show a strong directional sensitivity. The direction of peak correlation is different at different sites and is consistent with the direction of power lines. Correlation coefficients for datasets of peak 1-h or 3-h values were higher than for 1-min datasets. This shows that there is a closer relationship between the envelopes of geomagnetic disturbances and GIC than between the detailed variations themselves.

April 2000 geomagnetic storm: ionospheric drivers of large geomagnetically induced currents

Abstract. Geomagnetically induced currents (GIC) flowing in technological systems on the ground are a direct manifestation of space weather. Due to the proximity of very dynamic ionospheric current systems, GIC are of special interest at high latitudes, where they have been known to cause problems, for example, for normal operation of power transmission systems and buried pipelines. The basic physics underlying GIC, i.e. the magnetosphere – ionosphere interaction and electromagnetic induction in the ground, is already quite well known. However, no detailed study of the drivers of GIC has been carried out and little is known about the relative importance of different types of ionospheric current systems in terms of large GIC. In this study, the geomagnetic storm of 6–7 April 2000 is investigated. During this event, large GIC were measured in technological systems, both in Finland and in Great Britain. Therefore, this provides a basis for a detailed GIC study over a relatively large regional scale. By using GIC data and corresponding geomagnetic data from north European magnetometer networks, the ionospheric drivers of large GIC during the event were identified and analysed. Although most of the peak GIC during the storm were clearly related to substorm intensifications, there were no common characteristics discernible in substorm behaviour that could be associated with all the GIC peaks. For example, both very localized ionospheric currents structures, as well as relatively large-scale propagating structures were observed during the peaks in GIC. Only during the storm sudden commencement at the beginning of the event were large-scale GIC evident across northern Europe with coherent behaviour. The typical duration of peaks in GIC was also quite short, varying between 2–15 min.Key words. Geomagnetism and paleo-magnetism (geomagnetic induction) – Ionosphere (ionospheric disturbances) – Magnetospheric physics (storms and substorms)