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Record W6992643268

Metrology and the elctric power grid modernization

2018· article· en· W6992643268 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNPARC · 2018
Typearticle
Languageen
FieldEngineering
TopicElectricity Theft Detection Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsElectricity meterSmart gridMetrologyElectric power systemElectric powerDistributed generationRenewable energyPower electronicsBlackoutPower engineering
DOInot available

Abstract

fetched live from OpenAlex

Metrology, as the science of measurement, is the very basis for acquiring scientific knowledge. In electric power systems, measurements of electrical and non-electrical quantities are necessary for monitoring, control, protection, and sage and reliable operation. Another significant application is revenue metering for industrial, commercial and residential customers. In today’s interdependent world, ensuring uniform metrology inside and across national boundaries is an important enabling factor of national and international trade, including the electrical energy trade. The introduction of distributed power generation, renewable energy resources, and deregulation of electric power utilities has in many countries, been transforming the electric power grids. We are witnessing exciting developments in metrology, on which the Smart Grid is based. This includes smart metering, synchro phasor and frequency measurements, wide-area protection, wide-area situational awareness, digital substations, energy storage and other evolving power system technologies. The proliferation of harmonics in the grid has been increasing over the last decades. With the prominent role of power electronics in new Smart Grid developments, this trend continues. The increased penetration of electric vehicles (EV) and the EV infrastructure emphasizes the necessity for wide frequency band measurements of distorted waveforms. New instrumentation and measurement methods for industrial applications at high-voltage and high-current levels are being developed. The digital measurements of voltage, current, phase, frequency, power and energy are continually improving. This is pushing the boundaries of the high accuracy measurements needed for calibrations. The role of National Measurements Institutes in providing the highest accuracy measurement standards and traceability to SI units is essential. The SI is undergoing profound changes, and the new revised SI is about to be adopted. Metrology has a key role in the research, development and innovation of evolving electric power grid. In the words of Lord Kelvin: “If you cannot measure it, you cannot improve it.”

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score0.159

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 communication0.0000.000
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 head0.003
GPT teacher head0.185
Teacher spread0.182 · 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