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Design and simulation of a hybrid energy system for Ramea Island, Newfoundland

2022· article· en· W4309640152 on OpenAlexaffabout
Siddhanth Kotian, Afreen Maliat, Abdul Azeez

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSizingDiesel generatorRenewable energyAutomotive engineeringHybrid systemWind powerMATLABMarine engineeringElectric power systemHybrid powerEnergy storageComputer scienceDiesel fuelEngineeringPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Renewable energy systems are widespread due to declining costs and rising efficiency. This research examines the design, optimal sizing, and control of a Hybrid Power system to replace the current wind-diesel system of Ramea Island. The wind turbines of the current system are now not operational. It also has a hydrogen-based storage system and generator that is not operational. In this research, we proposed a new storage system model for the Island. The proposed Hybrid energy system, includes Solar powered PV, Wind turbines, Battery storage, and a Diesel generator. The target system is analyzed in different applications like RETScreen, REopt, and Homer Pro. MATLAB Simulink is used for dynamic modeling of the proposed system design. All the components are designed and simulated in MATLAB/Simulink. Design and simulation results are included in this paper.

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 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: none
Teacher disagreement score0.946
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)0.0000.000

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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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.

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

Citations7
Published2022
Admission routes2
Has abstractyes

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