Modeling of a Photovoltaic-Powered Electric Vehicle Charging Station with Vehicle-to-Grid Implementation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper is aimed at modelling of a distinct smart charging station for electric vehicles (EVs) that is suitable for DC quick EV charging while ensuring minimum stress on the power grid. Operation of the charging station is managed in such a way that it is either supplied by photovoltaic (PV) power or the power grid, and the vehicle-to-grid (V2G) is also implemented for improving the stability of the grid during peak load hours. The PV interfaced DC/DC converter and grid interfaced DC/AC bidirectional converter share a DC bus. A smooth transition of one operating mode to another demonstrates the effectiveness of the employed control strategy. Modelling and control of the different components are explained and are implemented in Simulink. Simulations illustrate the feasible behaviour of the charging station under all operating modes in terms of the four-way interaction among PV, EVs and the grid along with V2G operation. Additionally, a business model is discussed with comprehensive analysis of cost estimation for the deployment of charging facilities in a residential area. It has been recognized that EVs bring new opportunities in terms of providing regulation services and consumption flexibility by varying the recharging power at a certain time instant. The paper also discusses the potential financial incentives required to inspire EV owners for active participation in the demand response mechanism.
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.
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 it