A Cyber-Physical Control Framework for Transient Stability in Smart Grids
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Bibliographic record
Abstract
Denial of service attacks and communication latency pose challenges for the operation of control systems within power systems. Specifically, excessive delay between sensors and controllers can substantially worsen the performance of distributed control schemes. In this paper, we propose a framework for delay-resilient cyber-physical control of smart grid systems for transient stability applications. The proposed control scheme adapts its structure depending on the value of the latency. As an example, we consider a parametric feedback linearization (PFL) control paradigm and make it “cyber-aware.” A delay-adaptive design that capitalizes on the features of PFL control is presented to enhance the time-delay tolerance of the power system. Depending on the information latency present in the smart grid, the parameters and the structure of the PFL controller are adapted accordingly to optimize performance. The improved resilience is demonstrated by applying the PFL controller to the New England 39-bus and WECC 9-bus test power systems following the occurrence of physical and cyber disturbances. Numerical results show that the proposed cyber-physical controller can tolerate substantial delays without noticeable performance degradation.
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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) | 0.000 | 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 | 0.000 | 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 it