Flexible Time-Stepping Dynamic Emulation of AC/DC Grid for Faster-Than-SCADA Applications
Bibliographic record
Abstract
Dynamic simulation of the integrated AC/DC grids plays a crucial role in the energy control center. In this work, a faster than supervisory control and data acquisition (FT-SCADA) emulation based on flexible time-stepping (FTS) algorithm is proposed for the energy control center to predict and mitigate the impacts after serious disturbances using field-programmable gate arrays (FPGAs). To gain a high acceleration over SCADA/realtime, the FTS-based dynamic emulation is applied to the AC grid, which is the IEEE 118-bus system where a 9 -order synchronous machine model is adopted. Meanwhile, the electromagnetic transient (EMT) emulation revealing the exact performance of the DC grid provides an insight into the impact on its AC counterpart. A power-voltage interface is inserted between the AC and DC grids since distinct emulation strategies are utilized, and the EMT-dynamic co-emulation is able to run concurrently on FPGA boards due to their massive parallelism. Three case studies are emulated to demonstrate the efficacy of the proposed algorithm, and a minimum of 101 times faster-than-SCADA/real-time can be achieved. Hence, following the occurrence of a disturbance, the FT-SCADA/RT emulator will generate an optimal solution in advance to maintain the stability of the hybrid AC/DC grid. The esults of the FTS-based FT-SCADA/RT emulati <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">onareva</sup> lidated by the off-line transient stability simulation tool TSAT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> of the DSATools suite.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".