Control Design for Effective Usage of Electric Vehicles in V2G-Enabled DC Charging Stations
Bibliographic record
Abstract
This article discusses the usage of electric vehicles (EVs) to enable vehicle-to-grid (V2G) in DC charging stations. The V2G-enabled DC charging station is equipped with bidirectional DC/DC converters for both DC chargers and the energy storage system (ESS) and a three-phase two-level AC/DC voltage source converter for connecting to the low-voltage grid. A proposed controller with a state-of-charge (SoC) balancing algorithm for a bidirectional DC charging station is designed to offer the capability to limit the injected power from the grid using both EVs in V2G mode (V2G-EV) and the ESS. It ensures the safety of each V2G-EV battery by communicating with the EV battery management system (BMS) and receiving its SoCs, charge/discharge current limits, and energy capacity. Finally, it aggregates EV batteries and the optional ESS using the proposed SoC balancing algorithm. Several cases are developed to evaluate the performance of the proposed control design in the studied DC charging station model. The results validate the performance of the control design in both offline simulation and controller-hardware-in-loop (C-HIL) implementation via a digital signal controller (DSC) and a real-time simulator.
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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 | 0.001 | 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) | 0.000 | 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".