Analytically Assessing the Effect of Strength on Temporary Overvoltage in Hybrid Multi-Infeed HVdc Systems
Bibliographic record
Abstract
In hybrid multi-infeed HVdc (HMIDC) systems comprising both voltage-source and line-commutated converters’ inverters, the strength has a significant effect on the temporary overvoltage (TOV). However, this effect has always been assessed by the simulated approach in earlier works. It is unable to provide the sufficiently theoretical perspectives and also time-consuming as onerous electromagnetic transient simulations are required. Therefore, in this letter, the mathematical expression of the TOV is first derived as the analytical function of the hybrid multi-infeed interactive effective short-circuit ratio (HMIESCR) strength index. This derivation is achieved by using the quasi-steady-state analytical model of HMIDC systems with the interinverter interactions considered. Then, the derived expression is utilized for analytically assessing the effect of the HMIESCR on the TOV versus various system parameters and operation variables. Compared to the simulated approach, the proposed analytical approach here can offer more sufficiently theoretical perspectives and is also more efficient as simulations are no more required. Finally, the experimental results of a hybrid tri-infeed HVdc test system based on the hardware-in-the-loop platform validate the analytical approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".