Model Prediction Adaptive Control for wide-area power system stability enhancement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing additions of large-scale, non-traditional dispersed electricity generations such as those from wind farms on the traditional power systems have raised considerable concerns about the stability of power systems and adequacy of conventional stability controls. This paper presents an efficient adaptive stability control, based on step-ahead model prediction methodology, for a wide-area power system with multiple generators and distribution systems including dispersed generations. This control named Model Prediction Adaptive Control (MPAC) is built upon optimization of selected performance index defined as weighted combination of generator voltage deviation, mechanical-electrical torque mismatch, and speed incremental. The paper demonstrates effectiveness of MPAC for improvement of the wide-area power system stability. This paper offers unique stability studies for wide-area power systems subjected to disturbances and dynamic dispersed generations simultaneously. This paper presents the new concept, design, and case studies of MPAC. Comprehensive illustration of efficiency of MPAC versus existing methods is provided.
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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