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Record W1965347154 · doi:10.1109/tsg.2010.2066293

Power Electronic Signaling Technology—A New Class of Power Electronics Applications

2010· article· en· W1965347154 on OpenAlexaff
Wilsun Xu, Wencong Wang

Bibliographic record

VenueIEEE Transactions on Smart Grid · 2010
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPower electronicsElectrical engineeringSmart gridElectronicsPower engineeringElectric power transmissionComputer sciencePower transmissionPower (physics)Electric power systemClass (philosophy)EngineeringElectronic engineeringTelecommunicationsPower factorVoltage

Abstract

fetched live from OpenAlex

The application of power electronics to facilitate the transmission or conversion of electric energy has been well known. This paper presents a different class of power electronic applications-the power electronic circuits are deployed to create small but discernible signals online. The signals are utilized for monitoring, power line communication and other information-oriented purposes. We use the term “power electronic (PE) signaling technology” to designate the technologies involved in these applications. The objective of this paper is to survey and review the developments in this fascinating field. Several highly successful PE signaling technologies and their applications are illustrated. It is believed that signaling-oriented power electronic techniques will have many potential applications in power systems and can be a major source of innovation for the smart grid initiative.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.004
GPT teacher head0.199
Teacher spread0.196 · 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 designTheoretical or conceptual
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

Citations24
Published2010
Admission routes1
Has abstractyes

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