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Record W2045715296 · doi:10.5539/mas.v4n8p33

Application of Differential Evolution for Congestion Management in Power System

2010· article· en· W2045715296 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCongestion managementParticle swarm optimizationDifferential evolutionComputer scienceReliability (semiconductor)Electric power systemMathematical optimizationElectricity marketDatabase transactionElectricityDifferential (mechanical device)Work (physics)Order (exchange)Management systemOperations researchReliability engineeringPower (physics)AlgorithmOperations managementMathematicsBusinessEconomicsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. This paper proposes an algorithm for congestion management in a pool based electricity market based on differential evolution (DE). The aim of the proposed work is to minimize deviations from preferred transaction schedules and hence the congestion cost. Numerical results on test system namely IEEE 30 Bus System is presented for illustration purpose and the results are compared with Particle swarm optimization (PSO) in terms of solution quality. The comprehensive experimental results prove that the DE is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.345

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 integrity0.0000.000
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 head0.003
GPT teacher head0.192
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