Toward Flexible Risk-Limiting Operation of Multi-Terminal HVDC Grids With Vast Wind Generation
Bibliographic record
Abstract
Contingencies occurring in multi-terminal high voltage direct current (MT-HVDC) grids can result in DC voltage/flow violations and also affect the frequency stability of the connected multiple asynchronous grids. To recognize and control such notable operating risks, a novel flexible risk-limiting optimal power flow (FROPF) for the MT-HVDC grid with vast wind generation is proposed in this paper. Within the two-stage FROPF structure, the pre-contingency operation of grid-side voltage-source converters (GVSCs) is optimized to minimize MT-HVDC grid power losses. Immediately following an outage occurring in the MT-HVDC grid, various fast-acting corrective actions of GVSCs are utilized to hedge against the overall risk exposure, including the wind power curtailment risk of the MT-HVDC grid and the rate-of-change-of-frequency (RoCoF) violation risk imposed on associated asynchronous grids. Reformulation techniques are introduced to ease the computational complexity of the optimization model. Case studies of two MT-HVDC grids demonstrate the effectiveness of the proposed FROPF.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".