Impact of Level 2 EV Charging on Phase Unbalance in Distribution Networks
Bibliographic record
Abstract
The rapid growth of single-phase EV charging can lead to significant time-varying phase unbalance in distribution grids. In this study, a distribution grid analysis is carried out on a planned Level 2 charger parking lot, located in the Simon Fraser University campus. Historical charging data from existing chargers at the university is used in order to estimate the phase unbalance produced by the new chargers over a 24-hour period. Two types of Level 2 chargers are considered for the new parking lot: a standard level 2 (L2) and a higher voltage level 2 charger with auto transformer (L2T). Both charger scenarios are seen to produce significant unbalanced currents which propagate to the substation and exceed recommended limits regularly throughout the day. This unbalance is seen to be significantly reduced and at times even eradicated by placing a power redistribution converter in the parking lot.
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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".