On the inefficiency of vehicle-to-grid (V2G) power flow: Potential barriers and possible research directions
Bibliographic record
Abstract
Transition to electric vehicles (EVs) is already under way. EVs are equipped with a drive train that is completely electric powered, with a fairly large on-board battery pack. More recently, EVs have been looked at as distributed sources of energy, whereby they could back up the power grid during critical high demand periods. With the help of an on-board battery pack, EVs can act as distributed generators and feedback energy to the AC grid. However, efficiency of energy conversion could become an issue in this power flow. Hence, vehicle-to-grid (V2G) power flow requires a detailed stage-by-stage efficiency analysis, to evaluate practical feasibility. This paper aims at introducing some of the issues in connecting battery-powered EVs to the electricity grid. The paper highlights few of the inefficiencies of V2G connection, especially from the point of view of power electronics converter energy conversion stages, and suggests some research directions for the near future, in order to possibly make V2G a practical reality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".