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Remote Terminal Units for Distribution Automation: Development and Commissioning Experience

2008· article· en· W2020285857 on OpenAlexaff
Ruchi Gupta, S.C. Srivastava, Rajiv K. Varma

Bibliographic record

VenueInternational Journal of Computers and Applications · 2008
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsWestern University
FundersMinistry of Education, IndiaIndian Institute of Technology Kanpur
KeywordsAutomationComputer scienceProject commissioningRemote controlProtocol (science)Terminal (telecommunication)Remote monitoring and controlProcess automation systemTelecommunicationsEmbedded systemControl (management)Operating systemEngineeringPublishing

Abstract

fetched live from OpenAlex

This paper describes indigenous design, development, and commissioning of Remote Terminal Units (RTUs) for computer-aided monitoring and control of 10 MVA power distribution network of Indian Institute of Technology Kanpur in India. RTUs play a significant role in data monitoring and control of the power distribution network from a remote location. Remote monitoring and control of the distribution system is also called Distribution Automation (DA). The developed and commissioned RTUs are based on an architecture that eliminates the requirement of DC transducer stage. This significantly reduces the cost and size of the RTU and the effort required during installation and commissioning of the RTU. The developed RTUs support the industry standard open protocol “Distributed Network Protocol (DNP3.0)” for data communication.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.256
Teacher spread0.237 · 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
GenreMethods

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

Citations3
Published2008
Admission routes1
Has abstractyes

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Same venueInternational Journal of Computers and ApplicationsSame topicIslanding Detection in Power SystemsFrench-language works237,207