Applicability of hybrid power systems for fishing vessels
Bibliographic record
Abstract
The shipping industry, including the fisheries sector, is under pressure to reduce its emission in order to keep pace with new global environmental regulations. In recent years great attention has been turned to the development of sustainable fisheries, especially in terms of fuel consumption reduction and following emission mitigation. Increasing the share of renewable energy sources, alternative fuels, monitoring devices and innovative technologies in general onboard ships is a common trend. Hybrid power systems can produce electricity from two or more sources, typically renewable ones. As a result, it can employ solar energy while the sun is out and another source, like wind, in cloudy weather, assuring a more consistent and effective supply. Also, the system can consist of a generator powered by two or more different forms of fuel (such as LNG, biodiesel, hydrogen…). A hybrid energy system is an effective strategy for moving away from economies that rely on fossil fuels. It is still an emerging technology, which is expected to evolve and thus have wider applicability and lower costs. However, the need for high-quality and detailed analysis of hybrid energy solutions has increased due to the great diversity of fishing vessels, different operational regimes, high investment costs, and the complexity of adapting the ship's energy system to new technologies. Given that the improvement of the Croatian fishing fleet in an environmental sense began recently, it is necessary to investigate possible hybrid energy configurations and analyze their advantages and disadvantages. This paper presents hybrid energy systems with: (a) series drivetrain; (b) parallel drivetrain; (c) series-parallel drivetrain. Their characteristics and effect on the ships' power system are explained in detail. As an example, the implementation of a series hybrid energy systems on a fishing vessel operating in the Adriatic Sea is presented, along with the environmental and economic strengths this type of power system could provide.
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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 | 0.000 | 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) | 0.002 | 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".