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Record W2080734550 · doi:10.1109/ccece.2010.5575197

A priority-ordered constrained search technique for optimal distributed generation allocation in radial distribution feeder systems

2010· article· en· W2080734550 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
TopicOptimal Power Flow Distribution
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMathematical optimizationComputer scienceHeuristicPopulationDistributed generationQuality (philosophy)AlgorithmEngineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents a priority-ordered constrained search technique for optimal distributed generation (DG) allocation in radial distribution feeder systems. The distribution feeder system is divided into regions and the region(s) representing ≥ 40% of loads-percentage are selected for optimal DG placement. Utilizing the proposed technique with meta-heuristic algorithms will accelerate the algorithms' performance without affecting the solution quality. The artificial bee colony (ABC), as a new meta-heuristic population-based algorithm, is adopted to verify the proposed technique efficiency. The IEEE 33-bus and 69-bus feeder systems are examined, and the results obtained by the proposed technique are compared with those found using other methods. The outcomes confirm that the proposed technique led to significant search-space and time-consumption reductions without affecting the solution quality.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.248
Teacher spread0.236 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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