Development of an improved low frequency transformer model for use in GIC studies
Bibliographic record
Abstract
Geomagnetically Induced Currents (GIC) are the ground effect of a complicated space weather chain that originates in the sun. During a GIC event, the quasi dc current that enters the transformers through the grounded neutral can cause severe half cycle saturation in the iron core. This results in increased reactive power consumption and generation of significant levels of harmonic currents. A severe GIC event in 1989 caused a complete blackout in the Hydro-Quebec system, and it shows how vulnerable a power system can be. There have been many simulation studies carried out to model the effects of GIC in power systems using electromagnetic transient simulation programmes. Many of these attempts have used curve fitting techniques to model the hysteresis characteristics of power transformers. However, the correct representation of the hysteresis, including the long term remanence and recoil loops is important, since the source of the harmonic generation is the transformer itself. Therefore, the main objective of this work is to develop a simulation model of a power transformer that represents hysteresis characteristics including long term remanence and recoil loops. Further, the new model is used in simulation studies to analyse the effects of GIC in â power system. The new model is based on the Jiles Atherton (JA) theory of ferromagnetic hysteresis. The eddy current effects are also incorporated into the same model, so that the simulated B-H loop is frequency dependent. The new model is implemented using the transient simulation software PSCAD/ENITDC, and it is validated by comparing simulation results with recorded waveforms. A good agreement is achieved between the simulated and recorded waveforms. Effects of GIC on a power system are analyzed using a simulation model of a power system. Simulation studies show that a transient simulation carried out to model a GIC event requires not only the magnitude of the quasi dc current, but also its history with respect to any particular point of interest. Further, simulation studies demonstrate that it is important to accurately model the remanence effects of the iron core of power transformers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".