Big-Data Modeling Based Simscape Power Systems-ST for Protective Relaying
Bibliographic record
Abstract
This paper introduces novel methodologies for generating Big Data using specialized technology libraries (SPS-ST) in Matlab/Simscape Power Systems. A dedicated Matlab script is developed for simulating three IEEE standard benchmarks. Thousands of contingencies, such as line faults, generator losses, and load switches, are simulated to generate the database. During each simulation, twelve pieces of information are recorded to facilitate the implementation of artificial intelligence-based relay algorithms and the identification of early catastrophic indicators of the power systems stability. Furthermore, this database allows to modernize and develop the new protections functions. The load-flow convergence and dynamic systems response serve as criteria for verifying the correctness of implementation. The IEEE 39, 68 and 145 test systems with solar photovoltaic power plant (WECC PV) integration can be used to generate extensive training and testing databases simultaneously. The model is available in Matlab-Central file exchange platform, facilitating power systems training, research, and development endeavors.
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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) | 0.000 | 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 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".