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A Development of Integrated Offshore Floating Photovoltaic System with Wind-Solar Farm Designs Using Green Hydrogen and Electricity

2025· article· W7129409912 on OpenAlexaff
Govindaraj R, Ashraf Shaqadan, A Bulli Babu, Devolla Manogna, Aravinda K

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsPhotovoltaic systemRenewable energyOffshore wind powerTurbineWind powerSolar energyElectricity generationWind speed

Abstract

fetched live from OpenAlex

The IFPVWS is proposed to enhance offshore renewable energy generation by combining floating solar photovoltaic (FPV) systems with offshore wind turbines. This study utilizes high-resolution wind speed data over Spanish waters, focusing on historical and projected periods under two climate scenarios. The research includes determining wind power density, designing turbine spacing to mitigate wake effects, and minimizing energy costs through optimization techniques. The output from the solar component is modelled through variables including solar irradiance and temperature effects. The system also implements energy management strategies and conducts optimization using an optimization algorithm, accounting for system variables and performance across different metrics. The performance of the IFPVWS model was assessed by comparing wind park energy and solar park energy to total park energy. This evaluation included calculations for wind speed, solar radiation, and load power.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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
GenreMethods

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
Published2025
Admission routes1
Has abstractyes

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