Non-pilot Protection of the HVDC Grid
Bibliographic record
Abstract
This thesis develops a non-pilot protection system for the next generation power transmission system, the High-Voltage Direct Current (HVDC) grid. The HVDC grid protection system is required to be (i) adequately fast to prevent damages and/or converter blocking and (ii) reliable to minimize the impacts of faults. This study is mainly focused on the Modular Multilevel Converter (MMC) -based HVDC grid since the MMC is considered as the building block of the future HVDC systems. The studies reported in this thesis include (i) developing an enhanced equivalent model of the MMC to enable accurate representation of its DC-side fault response, (ii) developing a realistic HVDC-AC test system that includes a five-terminal MMC-based HVDC grid embedded in a large interconnected AC network, (iii) investigating the transient response of the developed test system to AC-side and DC-side disturbances in order to determine the HVDC grid protection requirements, (iv) investigating the fault surge propagation in the HVDC grid to determine the impacts of the DC-side fault location on the measured signals at each relay location, (v) designing a protection algorithm that detects and locates DC-side faults reliably and sufficiently fast to prevent relay malfunction and unnecessary blocking of the converters, and (vi) performing hardware-in-the-loop tests on the designed relay to verify its potential to be implemented in hardware. The results of the off-line time domain transients studies in the PSCAD software platform and the real-time hardware-in-the-loop tests using an enhanced version of the RTDS platform indicate that the developed HVDC grid relay meets all technical requirements including speed, dependability, security, selectivity, and robustness. Moreover, the developed protection algorithm does not impose considerable computational burden on the hardware.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".