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Record W2148045792 · doi:10.1109/pes.2008.4596062

A methodology for evaluation of permissible depth of penetration of distributed generation in urban distribution systems

2008· article· en· W2148045792 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversity of TorontoHydro One (Canada)
Fundersnot available
KeywordsAmpacityDistributed generationRenewable energyElectricity generationGridComputer scienceElectric power systemPenetration (warfare)Reliability engineeringEnvironmental scienceElectrical engineeringEngineeringOperations researchPower (physics)Mathematics

Abstract

fetched live from OpenAlex

Distributed generation (DG) promises potential benefits such as clean or renewable generation, grid support, and transmission and distribution deferral for distribution utilities. However, its integration into the passive distribution system has equal potential to cause adverse impacts. This paper presents the results from a joint study between Toronto Hydro Electric System Ltd. and the University of Toronto, to devise a methodology to evaluate the permissible depth of penetration of DG on Toronto Hydropsilas urban distribution system. The impact of conventional generation, and the addition of large amounts of PV-based generation, is studied. Issues relating to ampacity, voltage regulation, short circuit current are simulated in CYMDIST. The limitations to the depth of penetration are identified. Practical optimal locating of DG and impacts towards power quality and protection are also discussed.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.477

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 head0.138
GPT teacher head0.327
Teacher spread0.189 · 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

Citations14
Published2008
Admission routes2
Has abstractyes

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