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Record W1831589860 · doi:10.1109/lescpe.2003.1204670

Transaction impact analysis and its application in electricity markets

2003· article· en· W1831589860 on OpenAlex
Hong Chen, Claudio A. Cañizares

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
TopicElectric Power System Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDatabase transactionElectricity marketElectricityComputer scienceTransmission systemTransmission (telecommunications)Security analysisElectric power systemCongestion managementElectric power transmissionIndex (typography)VoltageReliability engineeringComputer securityOperations researchTelecommunicationsElectrical engineeringEngineeringPower (physics)Database

Abstract

fetched live from OpenAlex

System security considerations are becoming more critical for healthy and efficient electricity market operation. This paper defines and quantitatively analyzes transaction impact based on a system security index (SSI), which is defined to properly represent system security, and thus detect transmission congestion, taking into account thermal, voltage and voltage stability constraints. A simple and efficient method to determine the most effective market rescheduling strategy for transmission congestion relief is also presented based on a transaction impact analysis. The proposed technique is tested in a 3-area test system and a 129-bus model of a realistic system.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.676
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.204
Teacher spread0.201 · 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

Citations6
Published2003
Admission routes1
Has abstractyes

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