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Record W2140919703 · doi:10.1109/pes.2003.1267219

A power system assessment tool for the deregulated electricity market

2004· article· en· W2140919703 on OpenAlexaffabout
G. Hamoud

Bibliographic record

Venue2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491) · 2004
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsHydro One (Canada)HydraTek (Canada)
Fundersnot available
KeywordsActivity-based costingElectricity marketReliability engineeringReliability (semiconductor)ElectricityComputer scienceElectric power systemSoftwareMaximum power transfer theoremElectric power industryOperations researchPower (physics)EngineeringElectrical engineeringBusiness

Abstract

fetched live from OpenAlex

A software program was developed by Hydro One (formally Ontario Hydro) primary for reliability and production costing assessment of bulk power systems. The program simulates the operation of the power system during a specific period of time (hour, week, month, etc.) taking into account the random failures of generators and circuits, economic dispatch, fixed power injections, load profile during the study period and limits imposed on the transmission network due to thermal, voltage and stability considerations. The software has been used in various planning and operational studies at Hydro One and recently in transfer capability and congestion studies related to the deregulated electricity market. This paper gives an overview of the program and illustrates how it can be used as a market simulator in the new environment. Two applications of the program are presented: one dealing with the assessment of available transfer capability and the other with the assessment of congestion cost and locational marginal pricing.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.032
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.004

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 head0.004
GPT teacher head0.200
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2004
Admission routes2
Has abstractyes

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