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Record W2536716938 · doi:10.1109/sge.2012.6463974

Wireless communication requirements selection according to PMUs data transmission standard for smart grid

2012· article· en· W2536716938 on OpenAlexaff
M.M. Eissa, Ali M. Allam, Mohammad Mahfouz, Hossam A. Gabbar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsSmart gridComputer scienceWirelessTransmission (telecommunications)Data transmissionComputer networkCommunications systemTelecommunicationsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Large power systems are facing new challenges, such as increasing penetration of renewable energy sources, in particular wind generation, growing demands, limited resources, and competitive electricity markets. Under these conditions, the large power systems have to be covered from the reliability of the protection coordination. Wireless communication tool to collect data from different units to cape with the world is proposed to solve the interconnected power system as wide area system from the protection to coordination and then control action. The paper introduces the communication performance for the wireless scheme used for collecting data from phase measuring units (PMUs). The performance of Long Term Evolution (LTE) from the point of view the communication standard and PMUs data transmission is discussed. PMUs data transmission parameters are studying. These parameters are compared with the performance of LTE communication network. The main wireless communication requirements to be applied on smart gird are given. The estimation of the performance of LTE in terms of latency and Bandwidth based on the standards from 3GPP is given.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.616
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.052
GPT teacher head0.307
Teacher spread0.255 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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