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Record W2145913843 · doi:10.1109/pes.2003.1270423

Power price in deregulated markets

2004· article· en· W2145913843 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

Venue2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491) · 2004
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsIncentiveEconomicsEveningMorningMarket priceMid priceConsistency (knowledge bases)Monetary economicsEconometricsPrice levelMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

We compare the diurnal pattern of power price for weekdays and weekends for 14 deregulated markets, and find significant differences. All markets show low early morning prices with one or more price peaks during the day and evening. North American markets show a weekday monotonic pattern; European and New Zealand markets show a "double peak" pattern. Markets differ in the ratio of daily maximum to minimum price and of average weekday to average weekend price, and hence have a different incentive for time shifting power consuming activities within and between days. Data were filtered to remove days of high or low price excursions. In some but not all markets both the average price and the diurnal price pattern change significantly; infrequent price excursions shape price patterns. Price shows a significant correlation to load in some but not all markets. Some deregulated markets have patterns that are consistent and predictable and encourage a customer to shape power consuming activities, while other markets show a far lower degree of consistency, and create a high incentive to hedge.

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: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.182
Teacher spread0.178 · 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