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Record W2127664368 · doi:10.1109/tpwrs.2007.894867

Pricing Energy and Reserves Using Stochastic Optimization in an Alternative Electricity Market

2007· article· en· W2127664368 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Waterloo
FundersIndependent Electricity System Operator
KeywordsActivity-based costingElectricity marketElectric power systemLinear programmingEnergy marketStochastic programmingElectricityElectricity pricingComputer scienceProfit (economics)Mathematical optimizationContingencyOperations researchEconomicsMicroeconomicsEngineeringElectrical engineeringMathematicsPower (physics)

Abstract

fetched live from OpenAlex

This paper presents a stochastic linear programming model that can be used for pricing in electrical energy and reserve markets. It addresses capacity, energy, and reserve dispatch problems that may arise from n-1 contingency scenarios. Possible market solutions focusing on generator compensation using real-time, day-ahead, and hybrid schemes are enumerated, along with opportunities for consumer pricing and transmission costing. This model is illustrated on a 6-bus test system as well as a larger 66-bus system representing the Ontario network. A key difference among schemes is the degree of risk to the generators, measured by variance in profit

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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