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Record W2167885813 · doi:10.1109/tpwrs.2003.818587

An Electricity Market With a Probabilistic Spinning Reserve Criterion

2004· article· en· W2167885813 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

VenueIEEE Transactions on Power Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsMcGill University
Fundersnot available
KeywordsProbabilistic logicClearingReliability (semiconductor)Mathematical optimizationElectricity marketMarket clearingElectric power systemPower system simulationComputationComputer scienceElectricityReliability engineeringMathematicsEngineeringPower (physics)AlgorithmEconomics

Abstract

fetched live from OpenAlex

This paper addresses the problem of reliability-constrained market-clearing in pool-based electricity markets with unit commitment. In general, probabilistic reliability criteria that implicitly set the reserve requirement are defined by the loss-of-load probability and by the expected load not served. As the computation of such metrics is complicated by their nonlinear and combinatorial nature, we introduce the notion of hybrid metrics based on the probabilities of loss-of-load due to single and double generation outages only. The reliability-constrained market-clearing problem can then be formulated as a mixed-integer linear program and solved with large-scale commercial solvers. Numerical tests with data from the IEEE Reliability Test System indicate that the new method is computationally efficient and produces market-clearing results with the desired probabilistic characteristics.

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 categoriesMeta-epidemiology (narrow)
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 score0.906
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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