Flexibility of controllable power transformers for managing wind uncertainty using robust adjustable linearised optimal power flow
Why this work is in the frame
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Bibliographic record
Abstract
As renewable energy sources (RESs) penetration increases in the power system, the transmission system operators face new challenges to ensure system reliability and flexibility while ensuring high utilisation of uncertain RES generation. Controllable transformers with on‐load tap changers and phase shifting capability are the promising flexibility tools to keep the system acceptable security and flexibility levels by controlling the voltage levels and energy flow. The AC optimal power flow (AC OPF) with detailed modelling considerations such as the bus voltage magnitude by including these devices is challenging. This study develops the AC OPF model to propose a robust flexibility optimisation framework for daily scheduling problem with uncertain wind energy sources. Nevertheless, the proposed formulation representation is an intractable mixed integer nonlinear programming (MINLP) while it includes AC grid constraints and the augmented modelling of the mentioned transformers. Accordingly, the proposed MINLP problem has been converted into a mixed‐integer linear program where a certain level of solution accuracy can be achieved for the available time budget. The effectiveness of the proposed method is demonstrated using a modified 6‐bus and IEEE 118‐bus test systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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