Data and Model Hybrid Driven Non-Intrusive Wideband Impedance Measurement for LCC-HVDC Systems
Bibliographic record
Abstract
Line commutated converter based high-voltage direct-current (LCC-HVDC) systems connected to weak grids are susceptible to wideband oscillations, threatening system stability. In this paper, a data driven modeling based non-intrusive wideband impedance measurement method is proposed for LCC-HVDC systems to monitor the dynamic characteristics of the receiving-end grid and assess the risk of wideband oscillations, without the need for additional primary equipment or external harmonic disturbances injection. First, the harmonic state-space (HSS) impedance model of LCC-HVDC is established, and the harmonic interaction mechanism between LCC system and the receiving-end grid is analyzed. Then, an impedance measurement method based on data-driven modeling is developed, incorporating an adaptive variable time-step (AVTS) sampling scheme and a dynamic frequency warping (DFW) technique to enable real-time assessment of oscillation risk profiles with reduced computational burden. Finally, the proposed method is validated by using the CIGRE benchmark system as well as the hardware-in-the-loop (HIL) tests.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".