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Record W2906229731 · doi:10.1109/pesgm.2018.8586222

Quantifying Reliability Contribution of an Energy Storage System to a Distribution System

2018· article· en· W2906229731 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Monte Carlo methodComputer scienceRenewable energyRange (aeronautics)DeferralPhotovoltaic systemEnergy storagePoint (geometry)Distributed generationEngineeringElectrical engineeringPower (physics)Statistics

Abstract

fetched live from OpenAlex

This paper presents a Monte-Carlo simulation based framework to quantify the reliability benefit brought by the integration of an Energy Storage System (ESS) to an active distribution system. The benefits associated with ESS integration, such as reliability improvement at load point and system level, the reliability worth, deferral of immediate distribution system expansion, and better utilization of renewable distributed generation resources are quantified using a suitable reliability model of ESS. Assessments are conducted on a radial distribution test network with photovoltaic arrays and ESS. A range of case studies are performed to assess the reliability contribution of ESS, and conclusions are drawn based on the results obtained.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.643

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 science0.0000.000
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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