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Record W1988327265 · doi:10.1109/ccece.2012.6335047

Optimization and a comparison between renewable and non-renewable energy systems for a telecommunication site

2012· article· en· W1988327265 on OpenAlexaffabout
Mohamed El Badawe, M. Tariq Iqbal, George K. I. Mann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRenewable energyDiesel generatorHybrid systemHybrid powerElectric power systemAutomotive engineeringComputer scienceEngineeringElectrical engineeringPower (physics)Diesel fuel

Abstract

fetched live from OpenAlex

The renewable energy based hybrid energy system is one of better solutions to reduce the environment pollution. Renewable energy offers power supply for locations that are remotely located and also allows economical way of producing power for small power applications. The objective of this paper is to optimize and compare a non-renewable energy system with a renewable energy system for a remotely located telecommunication site in Mulligan, Labrador in Canada. The current system is operated using a diesel generator and batteries and the proposed system expects to integrate a hybrid wind and solar energy system into the existing diesel generator and batteries. Hybrid Optimization Model for Electric Renewable (HOMER) software is used to obtain the most feasible configuration of a hybrid renewable energy system. The results show the hybrid renewable energy system is cost effective. The proposed system significantly reduces the running time of diesel generator and this helps to reduce the emission level. Moreover, it is expected that the proposed system will help the BellAliant Company to provide uninterrupted power for their sites in remote areas of Labrador.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.258
Teacher spread0.234 · 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 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

Citations15
Published2012
Admission routes2
Has abstractyes

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