Modelling and Performance Evaluation of the Virtual Air Gap Variable Reactor
Why this work is in the frame
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Bibliographic record
Abstract
This thesis describes a novel device, the Virtual Air Gap Variable Reactor (VAG-VR), which is capable of producing a continuously\nvariable reactance by locally saturating a small section of the reactor core via an embedded dc control winding. Variable Reactors have many applications in the power industry such as control of line power flow, voltage regulation, reactive line compensation and limiting inrush currents. A variable reactor is most commonly implemented as a thyristor controlled reactor (TCR) by switching in and out a constant reactance to achieve an averaged variable reactance. By using a virtual air gap, a continuously variable reactance is possible. The VAG-VR offers a better dynamic response, without introducing the harmonics created by the thyristor switching of a TCR. The VAG-VR gives low triplen harmonics and therefore allows control of reactive power in single phase or unbalanced three phase systems as would be required in the distribution system.\n\n\nAn experimental prototype VAG-VR was developed to investigate three main performance measures: steady state performance, dynamic response and harmonic performance. Over the operating range of the VAG-VR inductance was varied from 100% to 9% of its original value. The dynamic response of the VAG-VR is approximately one tenth of a cycle. This compares favorably to a TCR which responds in approximately half a cycle. Harmonics are also shown to be significantly reduced in the VAG-VR compared to the TCR.\n\n\nA dynamic model of the VAG-VR, suitable for incorporation into power system simulations, was developed and validated. Parameters were determined both experimentally and through finite element method (FEM) simulations. Both experimental and simulation results indicate that the VAG-VR offers a technically viable alternative to the TCR.
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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 it