MétaCan
Menu
Back to cohort
Record W1980021673 · doi:10.1155/2014/974682

Challenges in the Smart Grid Applications: An Overview

2014· article· en· W1980021673 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Distributed Sensor Networks · 2014
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of WindsorWestern University
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and Technology
KeywordsSmart gridComputer scienceReliability (semiconductor)Demand responseGridDistributed generationTransmission (telecommunications)Risk analysis (engineering)Distributed computingComputer securityReliability engineeringTelecommunicationsElectricityPower (physics)Renewable energyElectrical engineeringBusiness

Abstract

fetched live from OpenAlex

The smart grid is expected to revolutionize existing electrical grid by allowing two-way communications to improve efficiency, reliability, economics, and sustainability of the generation, transmission, and distribution of electrical power. However, issues associated with communication and management must be addressed before full benefits of the smart grid can be achieved. Furthermore, how to maximize the use of network resources and available power, how to ensure reliability and security, and how to provide self-healing capability need to be considered in the design of smart grids. In this paper, some features of the smart grid have been discussed such as communications, demand response, and security. Microgrids and issues with integration of distributed energy sources are also considered.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.698
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.039
GPT teacher head0.280
Teacher spread0.242 · 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