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Current Control Schemes for Grid Following Inverter-based Onshore Electrified Ship

2024· article· en· W4404564474 on OpenAlexafffund
V. A. Tran, Ngoc-Lam Vu, Thanh Vo–Duy, João Pedro F. Trovão, Bảo‐Huy Nguyễn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMaritime Transport Emissions and Efficiency
Canadian institutionsUniversité de Sherbrooke
FundersMitacsCanada Research Chairs
KeywordsCurrent (fluid)InverterGridControl (management)Computer scienceElectrical engineeringEngineeringVoltageGeology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.658
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.014
GPT teacher head0.263
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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