Current Control Schemes for Grid Following Inverter-based Onshore Electrified Ship
Bibliographic record
Abstract
In the context of environmental conservation and sustainable development goals, the shipping industry is transitioning towards renewable energy sources instead of fossil fuels. Equipping ships with batteries and connecting them to the onshore grid through inverter-based resources (IBR) offers numerous benefits, such as reducing greenhouse gas emissions and optimizing energy use. However, ensuring the quality and stability of the electrical current when connected to the grid presents significant challenges. This paper compares three electrical current control methods: inverter-side control, grid-side cascade control, and grid-side single control, to enhance the quality and stability of the electrical current from ship batteries when connected to the onshore grid (grid-following inverter) under both strong and weak grid scenarios. The model, developed through simulation using the Energetic Macroscopic Representation (EMR) method, provides valuable insights. The results of this study will aid in selecting appropriate control methods for ports, promoting the widespread adoption of sustainable practices in the shipping industry.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".