A Modified Bus-Split Method for Aggregating Distributed Generation Units
Bibliographic record
Abstract
This paper presents the development and performance testing of a modified bus-split method for aggregating interconnected distributed generation units (DGUs). The modified bus-split method is developed by introducing power-based models for interconnected DGUs. The introduced power-based models are used to replace admittance-based models used in the original bussplit method. The developed power-based models are generalized for DGUs that are interconnected to a 1φ or a 3φ distribution network. The modified bus-split aggregation method can be beneficial for determining possible offsets of conventional power generation, as well as improving the management of peak-demand conditions. The injected power-based bus-split aggregation method is implemented for performance testing using collected data from several wind and photovoltaic energy conversion systems, which are interconnected at different locations of the distribution network. Test results demonstrate accurate and reliable aggregation without sensitivity to the interface type, power ratings, location, voltage level at the interconnection node, and/or configuration (1φ or 3φ).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".