Are Commercial EV Chargers Ready to Aid with Household Power Consumption?
Bibliographic record
Abstract
The transportation industry now accounts for approximately a quarter of worldwide energy-related direct CO2 emissions, and governments all around the globe have committed to converting their fossil-fuel vehicles to zero-emission ones by adopting electric vehicles. Current electric vehicles (EV) can store approximately 18 to 100 kWh of energy, which may be employed not only for commuting but also for other purposes such as delivering energy to households (V2H) or buildings (V2B), as well as offering ancillary services to the power grid (V2G). In this study, a real test setting including a trending bidirectional charger, an EV, a PV simulator, and household appliances are utilized to evaluate the performance of various V2H components and to learn about the concerns that may arise during V2H operation. The results of the tests on the bidirectional EV charger are presented in this paper. Although the results of the tests on the charger installed in the house are not satisfactory and consistent to the project’s goal, they are released in order to aid future studies in better understanding the true challenges of commercial bidirectional chargers.
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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 | 0.001 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".