Optimal sizing of battery energy storage systems in unbalanced distribution feeders
Bibliographic record
Abstract
This paper presents a mathematical model for optimal sizing of battery energy storage systems (BESS) in an unbalanced distribution system. The vanadium radox (VR) and sodium sulfur (NaS) based batteries are considered in this study. Detailed life-cycle cost analysis is carried out to first identify the long-term cost of the batteries, which is then included in the proposed model. Two case studies are carried out: first the effect of the local distribution company (LDC) savings on the battery size is examined, and second the optimal size of the battery is determined by solving a comprehensive optimization problem. The proposed model seeks to maximize the savings of the LDC accrued from BESS operation, i.e., maximize the difference of discharging and charging cost of the BESS, while the investment cost is minimized. The IEEE 13-node test feeder is used to test the proposed model.
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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".