Geomagnetic Induced Current Data Generation and Analysis in Power System Installations

: Geomagnetic induced current (GIC) is a ground end manifestation associated with the space weather perturbations that should be greatly taken into account by the society. Although the GICs implication to the power system is not regular, it can cause large scale of system failure. In equatorial, the power system is considered safe since the most intense of geomagnetic storm hap-pened in high latitude. However, the internal damage due to GICs which finally led to the South African power system failure has totally changed the normal perception. Therefore, a preliminary investigation on the GICs activity in equatorial region is performed to understand the space weather impact to the power system. Time derivative of the horizontal magnetic field component (dB/dt) is done to indicate the GICs activity value based on Faraday’s law. All the reported power failures are compiled to produce the threshold value of dB/dt, which possibly cause the harmful effect to the system. Then, dB/dt analysis is extended to show the pattern of GICs activity in function of magnetic latitude and local time. The results reveal that power network in equatorial region has possibly suffered by GIC. Plus, high number of intense GIC activity in this region occurred during dayside.


Introduction
The space weather perturbation is believed to affect the ground-based technology system in term of theoretical and experimental approached. The space weather perturbation mentioned above is the geomagnetically induced current (GIC). These GIC flow into the transformer architecture of the bulk power system through the winding where the current in the winding might be increased. More current formed in the winding, more magnetic flux might be generated and the core might be received a partial saturation on the part of the transformer. The partial saturation is believed to damage the working principle of the transformer (Fiori, Boteler, and Gillies 2014). The AC waveform might be misinterpreted, the protective relays might be desperation and drives to trip out the power transmission line. More so, affected by that, the stability problem, the voltage drop, also the power blackout moment is possible to occur. Rapidly mentioned the famous event in 1989 which is the Hydro -Quebec power transmission blackout and the society suffered for nine hours without electricity ., Jusoh, M. H., Yoshikawa, A., & Radzi, Z. M. (2018). The stimulation of the bulk power system enhances the consideration of awareness to identify to what extent the GIC can be impactful to the power transmission system (Ngwira et al. 2013). The rate of the change of the total magnetic field (dB/dt) normally used to identify the GIC level at high latitude region (Pulkkinen et al. 2017). The magnitude of dB/dt (nT/min) exceeding 30 nT was indicated the occurrence of the GIC. The high latitude regions are the one that achieves a high possibility that affected by the GIC event due to the auroral electrojet current as a driving mechanism. Previously, the dB/dt value during Hydro -Quebec power transmission is approximately 479 nT/min. Some of GIC cases, there was produced not only occurring due to the substorm, but the sudden impulse (SI) and the storm sudden commencement (SSC) also encourage the GIC to occur M. D., Miller, M, & Wilkinson, P. (2013), Goldthorpe, P, & Smith, E. A. (2012). The authors Kappenman, J. G. (2006) bring some information about the dB/dt value are not depending on the substorm as a single caused, but the SI event and the SSC had prepared the evidence that the value of dB/dt can still be high enough to penetrate in the power transmission system. This has been discussed by a great number of authors in literature, they proposed a model on how the ionospheric current penetrates in the lithosphere by applying the concept of Lorentz force. It has been reported that substations situated at the ends and at the corners of long transmission lines are prone to maximum GIC magnitudes Magnetic Components R. Ebora and N. Servando, (2009). These are the substations which are only connected to one substation on one end and a transmission line on the other end. However, a number of the study was done in a region close to the auroral zone and may not necessarily agree with regions far from the auroral zone. An investigation was done on the Namibian network and reported that south northerly lines appeared to be more susceptible to GICs The method had been used previously is by determining the time derivative of the horizontal component as conducted by P. J. Cilliers and C. T. Gaunt (2008), , R. Pirjola andA. Viljanen (2007) to determine the GIC phenomena. Meanwhile, other studies are done by calculation approached (Mohd Anuar et al. 2019). In addition, the on-site measurement that needs an equipment that must be conducted under the transmission line that operated with high voltage also had been used by (Piersanti et al. 2019). However, the space weather perturbation that drives GIC during the descending, peak, and ascending phases of the solar cycle is still questionable due to the different mode of solar activity. Traditionally, transmission lines protection has been done with the aid of relays. From the earliest types which were manually actuated to the present day where highly automated relays are commonly being used in numerous ways. The optimal coordination of primary and backup over-current relays (OCRs) scheme has become one of the main challenges in modern MV-distribution networks (DN) owing to the multi-looped structure and the increased penetration of interment nature-DGs with large-share capacities. The changeable operational topologies of microgrids in modern DN have increased the computational burden to obtain the optimal setting of OCRs. The discrimination time of OCRs scheme may be no longer sufficient or even unmanageable to provide reliable performance in the islanded and grid-connected operational modes. The numerous previously reported optimization techniques employed for OCR coordination may have some limitations/drawbacks regarding OCRs coordination and their framework. Therefore, this study provides a well-defined analytical examination of the limitations in the tripping characteristics of manufactured OCRs. A new constraint taking into consideration maximum plug setting multiplier (PSM) was proposed to improve the optimization techniques. Moreover, enhance the complementary with industrial OCRs tripping characteristics with the optimization techniques in term of coordination time interval  This work focuses on the transmission aspect of the electrical power value chain and considers primarily the protection of the system during faulty conditions of either overcurrent type or …with the underlying goal of mitigation. When simulating GIC in power systems one needs to approximate field strength of the geoelectric field at injection points, such as grounded transformers. It has been shown (Viljanen et al., 2004) that one can accurately estimate the geoelectric field components from the strength of the geomagnetic field and knowledge of the local ground conductivity. This is of practical interest since the magnetic field fluctuations are easier to measure than the actual geoelectric field strength. Here x and y is in the horizontal plane of the ground and the xaxis is northward pointing and the y-axis is eastward pointing (Zhao and Crossley 2020). Therefore, this study aims to observe and estimate the value of GIC by designing a GMD detection framework.

Materials and Methods
Having completed the review of the state of the art in Chapter two, certain unresolved challenges and gaps were identified whose solution have a potential for improving the mitigation of GIC on power system installations. Specifically where GMD have their sources in space weather related incidences which cause GIC that have been shown in section 3.2 to adversely affect the behavior of power systems, sometimes with catastrophic effects. During a GMD event, GIC may cause half-cycle saturation in certain high voltage power transformers, overheating (causes damage especially in older equipment), produce harmonics, increased reactive power requirements, protective power system mis-operation, loss of reactive power sources (static var, capacitors can be tripped) and potential for system collapse-blackouts.

Identification of the GIC functional expression from the acquired data
Fundamentally, the GIC phenomena is an electromagnetic phenomena. Therefore, it is guided by Maxwell's laws thus: Maxwell's equations are (microscopically) always valid. However, charges and currents are macroscopically usually divided into different types, and additional fields are introduced. The electric D field is related to E and the magnetic H field is related to B by constitutive equations, which are usually assumed to be linear and simple as follows: where µ and ε are the permeability and permittivity of the medium. The usual assumption in connection with geo-electromagnetic studies is that µ = µ0. Macroscopically, we can write Maxwell's equations similarly to (2)-(2.5) but µ0 and ε0 are replaced by µ and ε, and the charge density р = рfree and the current density j = jfree should only refer to charges moving freely in the medium. An additional constitutive equation needed in the geophysical part is the Ohm's law that relates jfree and E Where σ is the conductivity of the medium. What is still required for solving the geophysical part are the continuity conditions that enable moving from one medium to another. Usually we utilize the continuity of the tangential components of the E and H fields when moving across a boundary (Pirjola. R, 2012). The GIC is usually computed from the electric and magnetic field data using the formulas: Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 12 March 2021 doi:10.20944/preprints202103.0357.v1 The resulting GIC has been calculated as a function of the various electric field components by the formula where (Ex, Ey) are the horizontal components of the geoelectric field and (a, b) the system parameters. (a, b) that depend on the topology and electrical characteristics of the conductor system under investigation can be derived for individual locations by using information about the full conductor system ) parameters from GIC and ground magnetic field observations (Pulkkinen et al., 2007). The linear relation in Eq. (2.10) has been shown in numerous studies to hold to a good approximation in many situations of interest (Pulkkinen et al (Pulkkinen et al. ), 2006Ngwira et al., 2008;Pulkkinen et al., 2010). The typical values for (a, b) are in the range between 0-200 A•km/V (Pulkkinen et al., 2008), and references therein.

Results
The GIC expression which is used for computation is made possible by utilizing the measured magnetic field data from the center for atmospheric research (CAR) magnetometer station, Abuja, Nigeria. The resulting electric field values were also computed in the axes of the earth's plane (Ex and Ey) for this and stored accordingly in an excel file .Some of the obtained results are presented in this section. Finally the first GIC computation showing the induced currents as a function of the changes in magnetic field is given in Figure 2 above. Using the electric field equations for GIC computation, the following plots were obtained with the parameter set given in table 1 below

Discussion
Geomagnetic data has been acquired from the center for atmospheric sciences (CAR) Abuja. This data was sourced with the aid of a magnetometer instrument which is part of a network of magnetometers managed by CAR and engaged in data collection around the equatorial region. The collected data is saved on a desktop computer or laptop as Microsoft excel spreadsheet files using formats that are amenable to further data manipulation. The data which was used has been saved as an excel comma separated value (csv) file, having appropriate headers and data arranged in row-column format. The duration of data collected and used was for a period of twenty four hours (one day). The sample excel file will be described in terms of its row-columns size as being 1440 rows and 8 columns. The columns are all label in headers which describe the type of data being captured. The primary column names consist of timestamps, number of samples, date of the year, multi-axis GIC data and lastly quality control information. Of interest to this research is the GIC data which has been captured as a triplet of values representing the magnetic field strength in the x, y and z axes. This data is labeled in the header as Bx, By, Bz. Performing some data wrangling on the obtained data, it is necessary to ensure that the data is devoid of any elements that might prevent smooth training and analysis. Missing data samples and not-a-number (nan) entries are also processed to obtain a more representative dataset for modeling the GIC phenomena. This has been achieved with the aid of Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 12 March 2021 doi:10.20944/preprints202103.0357.v1 Python programming machine learning toolkit and the code listings can be found in the appendix A of this document. All supporting and derived data files are also available. The GIC is a measure of the level of induced current on the earth's magnetic field during the magnetic storm. It is measured as the quantity of charged energy particle in the magnetosphere. GIC will serve as an output to the system. 1440 data point of measurement for output data, with an hour sampling interval, recorded on a magnetometer was used for the modeling.