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Record W2012058488 · doi:10.1109/ccece.2010.5575237

Communication system for the remote hybrid power system in Ramea Newfoundland

2010· article· en· W2012058488 on OpenAlexafffundabout
Juan F. Acevedo, M. Tariq Iqbal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsMemorial University of Newfoundland
FundersMemorial University of NewfoundlandFederation for the Humanities and Social Sciences
KeywordsEthernetComputer scienceCommunications systemElectric power systemPower-line communicationBackupWirelessWind powerTransceiverHybrid powerElectrical engineeringEngineeringTelecommunicationsPower (physics)Computer network

Abstract

fetched live from OpenAlex

A reliable communication system is essential for the operation of a remote hybrid power system. Such system is needed to interconnect the wind turbines, diesel generators, and the hydrogen energy storage with a centralized supervisory controller and data acquisition system. For the purpose of this research, we have considered the remote wind-diesel-hydrogen hybrid power system currently under development at Ramea, Newfoundland. Communication methods such as Wireless Ethernet, Fiber Optic, Power Line Carrier, and low RF transceivers are analysed in order to decide the most efficient and low cost approach to a reliable communication solution. This paper illustrates the advantages of using power lines as communication carriers in addition to a collective transmission agreement with a wireless backup link which should have none or minimum transmission instabilities during a severe weather condition. The research also presents a description of parameters being measured by the data acquisition system at Ramea's remote wind-diesel-hydrogen energy solution.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.305

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.214
Teacher spread0.205 · 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 designNot applicable
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

Citations2
Published2010
Admission routes3
Has abstractyes

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