Distributed generation long-term planning for voltage profile enhancements using optimal hourly operation conditions
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
An algorithm to optimize distributed generation allocation in a long-term planning problem to purposely enhance hourly voltage profile is presented. This algorithm deploys an hourly optimal operation to fit the long-term planning problem. It requires the consideration of several operational factors both explicitly or as a byproduct. The complexity level of the problem and the degree of representation of variables (accuracy) necessitated the mixed integer nonlinear programming formulation. Case studies are performed to validate the proposed algorithm. Results confirm the potential benefits of the algorithm especially for distribution utilities interested in knowing the time, type (technology), location and size of DG units that can enhance voltage profile in an operational level.
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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 | 0.001 |
| 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