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RELIABILITY WORTH ASSESSMENT FOR DISTRIBUTION SYSTEMS: AUTOMATED VS. TRADITIONAL CONFIGURATIONS

2006· article· en· W2084623947 on OpenAlexvenueno aff
S. Conti, Giuseppe Marco Tina

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsnot available
Fundersnot available
KeywordsReliability (semiconductor)Profitability indexRestructuringComputer scienceReliability engineeringAutomationContext (archaeology)Quality (philosophy)Risk analysis (engineering)Service (business)Operations researchEngineeringEconomicsBusiness

Abstract

fetched live from OpenAlex

The influence of the electricity market on electrical distribution development determines new technical and legislative factors that limit the profitability of distribution companies. One of the main concerns for distribution companies, from both a technical and an economic viewpoint, is the regulations governing the quality of supply and, in particular, service continuity. In general, to cope with reliability requirements, it is necessary to invest in distribution restructuring, aiming at an optimal choice of operating schemes and management strategies, which often include telecontrol and automation in order to obtain improved continuity levels. In this context, distribution system reliability calculation is a crucial task: it enables utilities, on the one hand, to select the most appropriate configuration and operational procedure from various available options and, on the other, to predict the increased reliability obtainable by restructuring existing systems. To provide a wide basis for comparison between different network configurations and operational strategies, this article presents a study that highlights how telecontrol and automation affect the performance, in terms of various system reliability indices, of radial, open-loop, ring, and flower configurations. The information provided by evaluation of the reliability level at which different configurations can serve customers can be used in reliability worth assessments. Finally, the article briefly discusses how to use this information from the distributor's and the customers' point of view. In this latter perspective, an economic evaluation in terms of customer outage cost (COC) is 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.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

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