Detailed modelling, simulation and benchmarking of the voltage error detector circuit in the static excitation system of Manitoba Hydro's Long Spruce G. S. using PSCAD/EMTDC
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Bibliographic record
Abstract
Manitoba Hydro continues to refine a reliable model of its power system using PSCAD/EMTDC Testing Long Spruce detailed exciter model revealed an under-damped response not observed in field tests. In this paper, the cause of this oscillation is investigated and a solution proposed. In addition, a solution is proposed to include a voltage reference input to the model to allow for testing comparable to the field. A method to determine proper settings for the calibration potentiometers, which could be of use in the field as well as in simulations, was also developed The exciter model consists of several sub-modules representing the detailed functionality of actual control circuits, such as minimum excitation and volts/hertz limiters, stabilizer, current feedback, etc. Selective testing of each module showed the voltage error detector (VED) to be the cause of the oscillations. Mesh current analysis and other circuit analysis techniques were applied to establish an accurate transfer characteristic of the VED. The characteristic of the VED smoothing filter was determined to be unrealistic. The zener diodes were modeled as ideal, resulting in a non-linear transfer function. The voltage adjustment potentiometer was included to allow for user defined reference voltage settings. A conversion model was developed to convert the per-unit reference voltage setting to an adjustment potentiometer setting. The model was evaluated in open and closed loop step response simulations. Results were compared to field data for validation of the overall exciter. Including the nonlinear idealized behavior of the zener diodes improved the transfer characteristic for severe voltage drops in keeping with expected field operation.
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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 | 0.001 |
| 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