Solid State Transformers as Enhanced Smart Inverters for Power Quality Improvement in Active Distribution Networks
Bibliographic record
Abstract
Conventional voltage regulation strategies that use reactive or active power injection are ineffective in active distribution networks (ADNs) used as conventional power systems. This paper proposes a new way to operate solid-state transformers (SSTs) to improve voltage quality in active distribution networks (ADNs). The proposed control method uses the unused capacity of SSTs to regulate voltage in ADNs without adding any new hardware or overloading the SST. Since SSTs can participate in voltage regulation via reactive and active power control with the proposed method, they can be operated as “enhanced smart inverters” rather than smart inverters that provide voltage regulation service by reactive power regulation. In this paper, the fundamentals of the proposed method are explained and its effectiveness is confirmed with simulation results obtained from an IEEE 13 node test feeder modeled in MATLAB/SIMULINK.
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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".