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Record W2655712594 · doi:10.1109/ccece.2017.7946653

A comparison of low cost wireless communication methods for remote control of grid-tied converters

2017· article· en· W2655712594 on OpenAlexaff
Lasagani K A. Terashmila, George K. I. Mann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsConvertersWirelessComputer scienceGridRange (aeronautics)Electronic engineeringCommunications systemControl (management)Point (geometry)Computer networkTelecommunicationsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Remote control of grid tied converters has become important with an increasing number of grid connected energy storage systems. Hence, it is crucial point for utilities to outline the requirements of the communication methods and to find the best communication infrastructure to handle the remotely located converters in a reliable and cost effective manner throughout the operation. The purpose of this study is to come up with a low cost wireless communication solution for remote controlled converters. Focusing on low cost, this letter studies about three communication methods which can be applicable to control the remote converters. All three methods are being tested to find out the suitability for data communication. Then this paper provides a comparison of all three methods with cost, measured range and the data rate. And conclude that LoRa is the solution with the highest potential for this application from the compared methods.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.026
GPT teacher head0.351
Teacher spread0.325 · 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 designBench or experimental
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

Citations16
Published2017
Admission routes1
Has abstractyes

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