Geomagnetically Induced Currents Level Research Articles

Experimentally Validated Extended Kalman Filter Approach for Geomagnetically Induced Current Measurement

Geomagnetically induced currents (GICs) are referred to as the quasi-dc current flows in power networks, driven by complex space weather-related phenomena. Such currents are a potential threat to the power delivery capability of electrical grids. To mitigate the detrimental impacts of GICs on critical infrastructures, the GICs should be monitored in power systems. Being inherently dc from the power frequency point of view, the components of GICs are, however, challenging and costly to monitor in ac power grids. This article puts forward a novel methodology for the real-time estimation of GICs in power transformers. Such aim is attained by means of an extended Kalman filter (EKF)-based approach, mounted on the nonlinear state-space model of the transformer, whose parameters can be derived from standard tests. The proposed EKF-based algorithm employs the available measurements for the transformer differential protection. The proposed approach, relying on the differential current, can properly deal with the external sources of interference like harmonic excitation and loading. The EKF-based estimator presented is validated by simulation and experimental data. The results verify the ability of the proposed approach to robustly estimate the GIC level during various operating conditions.

Power system responses to geomagnetic disturbances recognized using phasor measurement recordings

Geomagnetically induced currents (GICs) flowing through transformers result in a DC bias, which poses a threat to safe and stable power grid operation. To evaluate the influence of geomagnetic storms on power systems, it is necessary to study actual power system responses. In this paper, the power system response is represented separately using current and reactive power measurements acquired using phasor measurement units (PMUs). On the basis of the data obtained from a wide-area measurement system, the power system responses to geomagnetic disturbances at Yangquan Substation, Shanxi, China were obtained. By employing the plane wave method, the data acquired during two mild magnetic storms at the Shisanling Geomagnetic Observatory were used to calculate the electric field and GIC at Yangquan Substation. The response variables and calculated GIC results agreed well, and the response variables were thus applied to assess the GIC level in the power system. The results show that the fluctuations in the PMU measurements were caused by GICs in the power system, laying the foundation for a significantly more detailed geomagnetic storm risk monitor.

Effects of Ionospheric Conductivity and Ground Conductance on Geomagnetically Induced Currents During Geomagnetic Storms: Case Studies at Low‐Latitude and Equatorial Regions

AbstractGeomagnetic field variations recorded by fluxgate magnetometers are used to evaluate geomagnetically induced currents (GICs) under the equatorial electrojet (EEJ) and South Atlantic Magnetic Anomaly (SAMA) during two geomagnetic storms in March and June 2015. Geomagnetic stations with information about the underground electrical conductivity structure and that can be approximated by unidimensional (1‐D) models for calculation of the geoelectric field are selected. GICs levels are estimated using a realistic local power grid model located in the central region of Brazil, artificially moved to the sites where the geomagnetic measurements are available. GIC magnitudes are not large during the storms, and a maximum amplitude of 3.8 A was estimated at an equatorial station positioned over high resistivity underground during the main phase of the June storm. Effects of the ionospheric currents over the measurement sites and of the conductivity distribution beneath these sites are also evaluated. It is observed that both (EEJ) and (SAMA) increase the GICs amplitudes, with the greatest effects associated with daytime (EEJ) currents. A cutoff frequency was identified for both the (EEJ) and (SAMA) so that signals with frequencies lower than 2 mHz (periods longer than 500 s) are not amplified by the ionospheric currents. In relation to the underlying conductivity structure, GIC magnitude is affected by variation of the surface impedance and the sampling rate of the geomagnetic field. In our case, differences in amplitude of the surface impedance at the Nyquist frequency control the relative effects of the ground conductance between the stations.

Long‐Lasting Geomagnetically Induced Currents and Harmonic Distortion Observed in New Zealand During the 7–8 September 2017 Disturbed Period

AbstractSeveral periods of geomagnetically induced currents (GICs) were detected in the Halfway Bush substation in Dunedin, South Island, New Zealand, as a result of intense geomagnetic storm activity during 6 to 9 September 2017. Unprecedented data coverage from a unique combination of instrumentation is analyzed, that is, measurements of GIC on the single‐phase bank transformer T4 located within the substation, nearby magnetic field perturbation measurements, very low frequency (VLF) wideband measurements detecting the presence of power system harmonics, and high‐voltage harmonic distortion measurements. Two solar wind shocks occurred within 25 hr, generating four distinct periods of GIC. Two of the GIC events were associated with the arrival of the shocks themselves. These generated large but short‐lived GIC effects that resulted in no observable harmonic generation. Nearby and more distant magnetometers showed good agreement in measuring these global‐scale magnetic field perturbations. However, two subsequent longer‐lasting GIC periods, up to 30 min in duration, generated harmonics detected by the VLF receiver systems, when GIC levels continuously exceeded 15 A in T4. Nearby and more distant magnetometers showed differences in their measurements of the magnetic field perturbations at these times, suggesting the influence of small‐scale ionospheric current structures close to Dunedin. VLF receiver systems picked up harmonics from the substation, up to the 30th harmonic, consistent with observed high‐voltage increases in even harmonic distortion, along with small decreases in odd harmonic distortion.

双电压等级电网GIC的相互作用特征

The mechanism of GIC (Geomagnetically Induced Current) is complex, which is influenced by a number of factors. In previous studies, when calculating GIC in a 500 kV power network, the 220 kV part of the network and voltage levels below are usually ignored. China launched the construction of 750 kV in 2005, and 1000 kV network in 2009. Such power networks consists of a large proportion of autotransformers, which enable direct electrical connection between the primary and secondary windings. Therefore, it is of great importance to study the GIC interaction between windings and the relative factors. We established GIC models according to the 750 and 330 kV power network as well as the 1000 kV and 500 kV network in Gansu province in China, using GIC Benchmark which is a standard testing case proposed in 2012. In our models, we adopted different scenarios where we chose to include or ignore the GIC from secondary windings. We calculated the GIC level in Gansu main network, 1000 kV and 500 kV networks under the geomagnetic storm in November 9 and 10, 2004. Comparative analysis was made between different scenarios to showcase the GIC interaction and its influence. Results revealed the characteristics of GIC interaction between two voltage levels, as well as GIC contribution from secondary windings in 750 and 1000 kV autotransformers, which will provide support to future researches in GIC calculation, risk evaluation of geomagnetic storms and GIC suppression in the power network.

GIC due to storm sudden commencement in low‐latitude high‐voltage power network in China: Observation and simulation

AbstractThe impact of geomagnetically induced currents (GICs) on the power networks at middle and low latitudes has attracted attention in recent years with the increase of large‐scale power networks. In this study, we report the GIC monitored at two low‐latitude 500 kV substations of China during the large storm of 17 March 2015. The GIC due to the storm sudden commencement (SSC) was much higher than that during the storm main phase. This phenomenon is more likely to happen at low‐latitude locations, highlighting the importance of SSC in inducing GIC in low‐latitude power networks. Furthermore, we ran a global MHD model to simulate the GIC during this SSC event by using the solar wind observation as input. The model results reproduced the main features of the GIC. The study also indicated that the eastward component of the geoelectric field is dominant for low‐latitude locations during the SSC events. Further, topology and electrical parameters of the power grids make significant differences in the GIC levels.

Enhanced Transformer Model for Low- and Mid-Frequency Transients—Part II: Validation and Simulation Results

The transformer model developed in Part I is validated based on the zero-sequence test data, a ferroresonance event, and the geomagnetically induced current (GIC) measurements. Various transformer core constructions, including single phase, three limb, five limb, conventional shell type, and seven-limb shell type are represented, based on the proposed transformer model. The simulation results show high accuracy of the proposed transformer model in representing the studied cases. The study reveals that the saturation of the transformers at a given GIC level is more severe than that predicted by the existing transformer models. Furthermore, the proposed transformer model clearly explains the reasons for the previously reported discrepancies between the GIC experimental and simulation results. The study also concludes that for an accurate transformer model, particularly for the three-limb core type, the detailed representation of the zero-sequence characteristic is an essential requirement. Such a characteristic can be obtained based on either the proposed approach of the paper or a zero-sequence dc excitation test in addition to the test data at the power frequency.

Regional estimation of geomagnetically induced currents based on the local magnetic or electric field

Previous studies have demonstrated a close relationship between the time derivative of the horizontal geomagnetic field vector (dH /dt ) and geomagnetically induced currents (GIC) at a nearby location in a power grid. Similarly, a high correlation exists between GIC and the local horizontal geoelectric field (E ), typically modelled from a measured magnetic field.Considering GIC forecasting, it is not feasible to assume that detailed prediction of time series will be possible. Instead, other measures summarising the activity level over a given period are preferable. In this paper, we consider the 30-min maximum of dH /dt or E as a local activity indicator (|dH /dt |30 or |E |30 ). Concerning GIC, we use the sum of currents through the neutral leads at substations and apply its 30-min maximum as a regional activity measure (GIC30 ).We show that |dH /dt |30 at a single point yields a proxy for GIC activity in a larger region. A practical consequence is that if |dH /dt |30 can be predicted at some point then it is also possible to assess the expected GIC level in the surrounding area. As is also demonstrated, |E |30 and GIC30 depend linearly on |dH /dt |30 , so there is no saturation with increasing geomagnetic activity contrary to often used activity indices.

Geomagnetically induced currents in Europe: Characteristics based on a local power grid model

We consider the model of the Finnish high‐voltage power grid in 1978–1979, for which the accurate parameters are available for calculating geomagnetically induced currents (GIC). Moving the grid at different locations across Europe gives estimates of GIC levels in this region. For calculating the geoelectric field driving GIC, we use different layered models of the ground conductivity and 1 min geomagnetic data of the year 2003. The results show a clear concentration of large GIC in north Europe, where the peak values are about 3–5 times larger than in Central and South Europe, being up to about 200 A in this specific power grid. There are two factors contributing to this finding. First, geomagnetic variations are generally stronger in the north. Second, there are regions in the north with clearly smaller ground conductivities than typically at other areas. Both of these reasons lead to larger electric fields in the north. A very similar behavior of GIC is found in the case when a single‐layered ground conductivity model is assumed everywhere. We also show that the geographic characteristics of GIC are quite insensitive to the details of the power grid model by modifying various parameters of the Finnish grid.

Comparison Study of the Geomagnetically Induced Current Level of Power Grid in Different Latitude

Geomagnetically induced current (GIC) relates to factors such as magnetic amplitude, geotecture and structure of power grid. On the basis of geotecture, according to the geomagnetic storm data of Dec 2006, employing the plan wave method, this paper finish the calculation of GIC level of 2012 Beijing planning power gird, and compare the result to the measure data of Shanghe substation, in Yanghuai transmission system. The comparison shows that power grid is much more affected by geotecture, direction and length of transmission line, grid topology and electrical parameters in mid-low latitude area

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.

Calculation of geomagnetically induced currents in mid‐ to low‐latitude power grids based on the plane wave method: A preliminary case study

Geomagnetically induced currents (GIC) with large amplitudes have been found flowing in the Yang‐Huai power transmission system, Jiangsu, and at the Ling'ao Nuclear Power Plant, Guangdong, China. In order to assess the effects of GIC, it is necessary to know the level of GIC in the power grids. In this paper, the main purpose of which is to introduce GIC observations and studies in such a mid‐ to low‐latitude country as China, the authors calculate GIC in the power grids on the basis of the simple Plane Wave Method and present a discrete algorithm according to which software has been developed to calculate the Earth surface electric field. The data of two strong magnetic storms at the Zhaoqing Geomagnetic Observatory are used to calculate the electric field and GIC at the Ling'ao Nuclear Power Plant. The measured data and the calculated results agree well, and calculations are thus applicable to assessing GIC in power grids. Additionally, the Heihe 220 kV power grid has been modeled to calculate GIC at three substations. The results show that the power grid topology and parameters are important factors for GIC levels in middle‐ and low‐latitude regions and even larger GIC may occur in these areas.

Solar activity and economic fundamentals: Evidence from 12 geographically disparate power grids

This study uses local (ground‐based) magnetometer data as a proxy for geomagnetically induced currents (GICs) to address whether there is a space weather/electricity market relationship in 12 geographically disparate power grids: Eirgrid, the power grid that serves the Republic of Ireland; Scottish and Southern Electricity, the power grid that served northern Scotland until April 2005; Scottish Power, the power grid that served southern Scotland until April 2005; the power grid that serves the Czech Republic; E.ON Netz, the transmission system operator in central Germany; the power grid in England and Wales; the power grid in New Zealand; the power grid that serves the vast proportion of the population in Australia; ISO New England, the power grid that serves New England; PJM, a power grid that over the sample period served all or parts of Delaware, Maryland, New Jersey, Ohio, Pennsylvania, Virginia, West Virginia, and the District of Columbia; NYISO, the power grid that serves New York State; and the power grid in the Netherlands. This study tests the hypothesis that GIC levels (proxied by the time variation of local magnetic field measurements (dH/dt)) and electricity grid conditions are related using Pearson's chi‐squared statistic. The metrics of power grid conditions include measures of electricity market imbalances, energy losses, congestion costs, and actions by system operators to restore grid stability. The results of the analysis indicate that real‐time market conditions in these power grids are statistically related with the GIC proxy.

Strong Magnetic Storm's Influence on China's Guangdong Power Grid

AbstractSince the Yang‐Huai power transmission system and other 500 kV long‐distance transmission lines coming into operation in 2001, unknown severe transformer vibration and increased noise have often been found in Shanghe of Jiangsu and Ling'ao of Guangdong. This paper gives a comparison of more than ten magnetic storms and measured transformer neutral current data since November, 2004, and proved that the disturbances were caused by geomagnetically‐induced current (GIC). On the 7th and 10th, November, 2004, the maximal magnetic storm caused GIC in Ling'ao Nuclear Station was 47A and 55.8A, both larger than the transformer neutral DC level in HVDC's monopole operation, so, magnetic storms' instantaneous influence is larger than HVDC's. And the data show that GIC level in Guangdong Power Grid is higher than that in Yang‐Huai power transmission system, the reason is considered to be related with grid structure and coast effect etc. By now, the widely concerned 1000kV UHV power transmission system has begun constructing, and the UHV line's unit resistance will be at most half of the 500 kV lines, and in condition of longer transmission line, larger scale and single‐phased transformer's adoption, the issue of magnetic storm's influences will be more urgent to be studied.

Surface electric fields and geomagnetically induced currents in the Scottish Power grid during the 30 October 2003 geomagnetic storm

A surface electric field model is used to estimate the UK surface E field during the 30 October 2003 severe geomagnetic storm. This model is coupled with a power grid model to determine the flow of geomagnetically induced currents (GIC) through the Scottish part of the UK grid. Model data are compared with GIC measurements at four sites in the power network. During this storm, measured and modeled GIC levels exceeded 40 A, and the surface electric field reached 5 V/km at sites in the United Kingdom (compared with quiet‐time levels of less than 0.1 V/km). The electric field and grid models now form part of a GIC monitoring, analysis, and warning software package with Web interface, developed for use by the grid operator. This package also contains a daily geomagnetic activity forecast service, a solar wind shock detector for geomagnetic storm warning, and a near‐real‐time geomagnetic data stream for storm monitoring.