Wide‐area voltage control system of flexible AC transmission system devices to prevent voltage collapse
Bibliographic record
Abstract
Hydro‐Québec has identified wide‐area control system as a key initiative able to significantly increase the voltage stability of its grid. In this context, an innovative project for wide‐area and local voltage control of shunt compensators was initiated. Its main objective is to implement a closed‐loop control system on Hydro‐Québec's network to optimise the reactive power support from the dynamic shunt compensators. The outcome of this project is the ‘global and local control of compensators’ (GLCCs) system which is based on synchrophasor technology and intelligent electronics devices. Applied to each shunt compensator of Hydro‐Québec's network, this robust voltage control system measures voltage variations in the load area and adjusts the operation set point of each shunt compensator accordingly, thus avoiding voltage collapse resulting from extreme contingencies. The GLCC control solution was intensively tested in simulation using PSSE software. Moreover, a pilot project was commissioned on a test bench replica of the system and also tested in real time using Hydro‐Québec's Hypersim digital simulator. Field tests of the GLCC were conducted on a −230/ + 660 MVars static vars compensator. The results of this pilot project were deemed conclusive and the deployment of the new voltage control system has been initiated by Hydro‐Québec.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".