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Record W4285265494 · doi:10.1109/mias.2022.3161000

Centralized Protection and Control System: Are We Ready for Deployment in the Chemical, Oil, and Gas Industry?

2022· article· en· W4285265494 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.

Bibliographic record

VenueIEEE Industry Applications Magazine · 2022
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsABB (Canada)
FundersABB
KeywordsSoftware deploymentEngineeringIEC 61850Control (management)Systems engineeringReliability engineeringComputer securityComputer scienceAutomationSoftware engineering

Abstract

fetched live from OpenAlex

This article discusses the recent trends and customer experience with the deployment of centralized protection and control (CPC) systems mainly by utility segment customers and its feasibility in the chemical, oil, and gas (COG) segment. (See “Abbreviations Used in This Article” for a list of abbreviations used throughout.) CPC represents a new approach to protection and control in power distribution networks—centralizing all protection and control functionality in one single device on the substation level. Being International Electrotechnical Commission (IEC) 61850-compliant and ready for future upgrades with the evolving grid, it supports optimal asset management. To demonstrate the improved utilization of technologies for CPC systems, this article describes (i) a new centralized/hybrid protection and control (HPC) scheme for the medium-voltage/low-voltage (MV/LV) network, (ii) benefits to substantially improve the “ease of operation and maintenance” of industrial plants, and (iii) supplier and end customer perspective with the pros and cons of this new CPC system and its feasibility for deployment in COG industries.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.543

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 integrity0.0000.001
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 head0.025
GPT teacher head0.242
Teacher spread0.217 · 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