Wide-Area Control of Power Systems Through Delayed Network Communication
Why this work is in the frame
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Bibliographic record
Abstract
Like general network communication, there are network-induced delays, data packet dropout and disordering in the communication of wide-area measurement systems. What impact do these factors have on the control of wide-area closed-loop power systems? This study aims at developing methods in order to take these factors into account in control of wide-area power systems. First, a networked control system model is constructed for wide-area closed-loop power systems; in this model, network-induced delays, data packet dropout, and disordering are captured by time-varying delays in wide-area measurement systems. Then, linear matrix inequality based methods are applied to design a controller for better power system performance using wide-area information as feedback signals. The controller can tolerate network-induced delays, data packet dropout, and disordering in the communication of wide-area measurement systems. Finally, we give some simulation results showing the effectiveness of our approach.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it