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Record W2605027696 · doi:10.1214/16-aoas1002

Electricity price dependence in New York State zones: A robust detrended correlation approach

2017· article· en· W2605027696 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

VenueThe Annals of Applied Statistics · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEconometricsElectricityDetrended fluctuation analysisGridEstimatorElectricity priceComputer scienceEconomicsStatisticsMathematics

Abstract

fetched live from OpenAlex

The cost of electricity varies across the zones of the New York State electric system. While fair and open access to the electrical grid is sought, we show that residents currently do not equally benefit, or suffer, from price changes. Upcoming major investments in the grid offer an opportunity to rectify these inequalities, but only if we understand the price-change propagation dynamics for the current underlying infrastructure. We study these dynamics, estimating the partial correlations between changes in electricity prices in connected zones. We develop and investigate a robust exponentially weighted correlation estimator that performs well in the presence of electricity price spikes and can track a rapidly changing time-varying correlation. We show that price-change partial correlations are mostly positive, but can also be negative, and provide new insight into price-change dynamics within the grid that cannot be extracted from the price-setting algorithm or obtained from available transmission capability data.

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: Methods · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.629

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 head0.057
GPT teacher head0.264
Teacher spread0.206 · 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