Impact of geomagnetic disturbances on power transformers: risk assessment of extreme events and data availability

Certain rare events can have a drastic impact on power systems. Such events are generally known as high-impact low-probability (HILP) events. It is challenging to predict the occurrence of a HILP event mainly due to lack of data or sparsity and scarcity of data points. Yet, it is essential to implement an evidence-driven asset management strategy. In this paper, event tree analysis is used to assess the risk of power transformer failure due to a geomagnetically induced currents (GIC). Those currents are caused by geomagnetic disturbances in Earth’s magnetic field due to solar activity. To assess the impact on power transformers, an understanding of the mechanism and sequence of sub-events that lead to failure is required to be able to construct an event tree. Based on the constructed event tree, mitigation actions can be derived. GIC blockers or reducers can be used. However, that would require extensive installation and maintenance efforts, and the impact on system reliability has to be studied. Also, such technology is still in its infancy and needs extensive validation. A suggested alternative is to combine early warning data from solar observatories with a load management plan to keep transformers below their rated operation point such that a DC offset due to GIC would not cause magnetic core saturation and overheating. Load management and the risk of early warning false positives can incur a negative effect on reliability. Nevertheless, the risk assessment performed in this paper show that incorporating load management in asset planning is a viable measure that would offset the probability of catastrophic failure.

Modelling of geomagnetically induced currents in the Czech transmission grid

We investigate the maximum expected magnitudes of the geomagnetically induced currents (GICs) in the Czech transmission power network. We compute a model utilising the Lehtinen–Pirjola method, considering the plane-wave model of the geoelectric field, and using the transmission network parameters kindly provided by the operator. We find that the maximum amplitudes expected in the nodes of the Czech transmission grid during the Halloween storm-like event are about 15 A. For the “extreme-storm” conditions with a 1-V/km geoelectric field, the expected maxima do not exceed 40 A. We speculate that the recently proven statistical correlation between the increased geomagnetic activity and anomaly rate in the power grid may be due to the repeated exposure of the devices to the low-amplitude GICs. Graphical Abstract

The Assessment of a Magnetizing-Current Inrush of a Power Transformer

The study aims to propose an analytical tool for determining the parameters of the power transformer magnetizing inrush current caused by geomagnetically induced currents flowing through high-voltage windings with a grounded neutral under the impact of geomagnetic disturbances on the power grid. The analytical equations for the instantaneous magnetizing current under geomagnetic disturbances were obtain by mathematical model of magnetizing branch for a shell-type power transformer. A model base on a magnetization characteristics piecewise-linear approximation for the electrical steel. The magnetizing inrush current amplitude and duration it was found depends on the intensity of geomagnetic disturbances and in cope-link with the dynamics of the power transformer core saturation transient process were determined the changes in the magnetizing inrush current amplitude and duration under geomagnetic disturbances. The magnetizing inrush current amplitude it was found may reach the level of short-circuit current periodic component at the point of power transformer grid connection. The results were verify by comparing the design and experimental values of the magnetizing inrush current amplitude. The advantages of proposed mathematical model shown with justifying the analogy between core saturation under connecting of power transformer to a grid and under geomagnetically induced currents exposed. The piecewise-linear approximation of power transformer magnetization characteristic, allow to obtain the amplitude value of magnetizing inrush current caused by geomagnetically induced currents with an accuracy of 6% and can be used with power grid steady state and transient simulation under geomagnetic disturbances.

The Lehtinen-Pirjola Method Modified for Efficient Modelling of Geomagnetically Induced Currents in Multiple Voltage Levels of a Power Network

The need for accurate assessment of the geomagnetic hazard to power systems is driving a requirement to model geomagnetically induced currents (GIC) in multiple voltage levels of a power network. The Lehtinen-Pirjola method for modelling GIC is widely used but was developed when the main aim was to model GIC in only the highest voltage level of a power network. Here we present a modification to the Lehtinen-Pirjola (LP) method designed to provide an efficient method for modelling GIC in multiple voltage levels. The LP method calculates the GIC flow to ground from each node. However, with a network involving multiple voltage levels many of the nodes are ungrounded, i.e. have infinite resistance to ground which is numerically inconvenient. The new modified Lehtinen-Pirjola (LPm) method replaces the earthing impedance matrix [Ze] with the corresponding earthing admittance matrix [Ye] in which the ungrounded nodes have zero admittance to ground. This is combined with the network admittance matrix [Yn] to give a combined matrix ([Yn]+[Ye]), which is a sparse symmetric positive definite matrix allowing efficient techniques, such as Cholesky decomposition, to be used to provide the nodal voltages. The nodal voltages are then used to calculate the GIC in the transformer windings and the transmission lines of the power network. The LPm method with Cholesky decomposition also provides an efficient method for calculating GIC at multiple time steps. Finally, the paper shows how software for the LP method can be easily converted to the LPm method and provides examples of calculations using the LPm method.

Reproducibility of the Geomagnetically Induced Currents at Middle Latitudes During Space Weather Disturbances

Watari et al. (Space Weather, 2009, 7) found that the geomagnetically induced current (GIC) in Hokkaido, Japan (35.7° geomagnetic latitude (GML)), is well correlated with the y-component magnetic field (By) (correlation coefficients >0.8) and poorly correlated with Bx,z and dBx,y,z/dt. The linear correlation with By would help predict the GIC, if we have capabilities of reproducing the magnetosphere–ionosphere currents during space weather disturbances. To validate the linear correlation with By for any periods (T) of disturbances, we made correlation analyses for the geomagnetic sudden commencements and pulsations (T = 1–10 min), quasi-periodic DP2 fluctuations (30 min), substorm positive bays (60 min), geomagnetic storms (1–20 h), and quiet-time diurnal variations (8 h). The linear correlation is found to be valid for short periods (cc > 0.8 for T < 1 h) but not for long periods (cc < 0.3 for T > 6 h). To reproduce the GIC with any periods, we constructed one-layer model with uniform conductor and calculated the electric field (IEF) induced by By using the convolution of dBy/dt and the step response of the conductor. The IEF is found to be correlated with the GIC for long periods (cc > 0.9), while the GIC-By correlation remains better for short periods. To improve the model, we constructed a two-layer model with highly conductive upper and less conductive lower layers. The IEF is shown to reproduce the GIC with cc > 0.9 for periods ranging from 1 min to 24 h. The model is applied to the GIC measured at lower latitudes in Japan (25.3° GML) with strong By dependence. The mechanism of the strong By dependence of the GIC remains an issue, but a possible mechanism for the daytime GIC is due to the zeroth-order transverse magnetic (TM0) mode in the Earth-ionosphere waveguide, by which the ionospheric currents are transmitted from the polar to equatorial ionosphere.