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Record W6999936268

Dynamic Modelling and Analysis of a Hybrid Power System of Floating Solar PV System for an Offshore Aquaculture Site in Newfoundland

2023· other· en· W6999936268 on OpenAlexaffabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSizingPhotovoltaic systemHybrid systemRenewable energyDiesel generatorMATLABElectric power systemHybrid powerSystem dynamicsAquaculture
DOInot available

Abstract

fetched live from OpenAlex

In this article a hybrid power system, a combination of \nsolar and diesel generator (DG) is modeled in MATLAB and the dynamic performance of the system are analyzed considering the design parameters. The said system is designed for an offshore aquaculture site located in Newfoundland, Canada. The paper presents a novel concept of evaluating the dynamic performance of floating solar PV panels over the water surface of the fish farm. The sizing and economic feasibility of the system were carried out on HomerPro. Design is modeled in MATLAB to analyze the impact of dynamic changes on system performance. The system is exposed to variable irradiance, temperature, and load side variations and simulated under each condition. The results presented here confirm the satisfactory and reliable response of the system in all scenarios. The designed system \nshall replace the existing power source (diesel gen) with green and economical energy resources and will be a great help to bring sustainability in the Canadian aquaculture 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.419

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.262
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2023
Admission routes2
Has abstractyes

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