Convex Model for Controlled Islanding in Transmission Expansion Planning to Improve Frequency Stability
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Bibliographic record
Abstract
Intentional controlled islanding (ICI) is the last resort to split an endangered power system into smaller islands to prevent blackout. New lines that are planned by transmission expansion planning (TEP) can affect the stability of islands during ICI. In this paper, an ICI-TEP method is proposed to improve the stability of islands by more efficient planning of transmission assets. Moreover, by developing a criterion for the frequency of center of inertia (COI) in each island, the frequency deviations of generators from the COI frequency are minimized to result in more stable islands. The proposed ICI-TEP, incorporating AC network representation, is modeled as mixed-integer linear programming and quadratic convex problems ensuring tractability. A Benders decomposition strategy is also proposed to solve the problem. Results of testing the proposed ICI-TEP method on IEEE 39-bus and 300-bus test systems confirm its effectiveness, compared to conventional TEP, in terms of coping with sever disturbances by creating more stable islands with a lower load shedding.
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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 | 0.000 | 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