Optimal allocation of distributed generation and reactive sources considering tap positions of voltage regulators as control variables
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
Abstract In this paper, by defining and solving an optimization problem, amount of distributed generators (DGs) and reactive power sources (RSs) in selected buses of a distribution system are computed to make up a given total of distributed generation for minimizing losses, line loadings, and total required reactive power capacity. The formulated problem is a combinatorial problem, therefore Tabu search algorithm is applied for solving the optimization problem. Results of solving the optimization problem for a radial 33‐bus distribution system and a meshed 6‐bus system are presented. When using less amount of reactive capacity, regarding tap positions of voltage regulators as control variables has considerable role in loss reduction and improvement of voltage profile. In the case of meshed systems, including line loadings in the cost function can significantly change results of solving the optimization problem such as amount of the required reactive capacity and how to assign DGs and RSs to the selected buses. Copyright © 2006 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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