Testing and validation of wide‐area control of STATCOM using real‐time digital simulator with hybrid HIL–SIL configuration
Bibliographic record
Abstract
This study presents a novel interfacing setup for testing and validating wide‐area monitoring and control (WAMC) techniques used in smart grids. The main purpose of this study is to provide a realistic approach for conducting WAMC studies. In here, a wide‐area controller (WAC) for a flexible AC transmission system (FACTS) device is implemented. The measurements for the WAC are collected using phasor measurements units (PMUs). Three main segments are being interfaced in this study. First, the real‐power grid, the local area controller of the actual FACTS device, and the PMUs are simulated using real‐time digital simulator. This simulation represents the central simulation and is interfaced with the WAC, which is realised using a MATLAB‐based program. This interface represents a novel software‐in‐the‐loop (SIL) scheme. On the other hand, an actual FACTS device is designed and interfaced to the central simulation via hardware‐in‐the‐loop (HIL) scheme. This SIL and HIL combination makes the experimental testbed more realistic and closer to the industrial standard. Various tests are conducted to examine the performance of the developed testbed.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".