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Record W2890869084 · doi:10.1086/686733

Intermittency and the Value of Renewable Energy

2016· preprint· en· W2890869084 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

VenueJournal of Political Economy · 2016
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsIntermittencyRenewable energyOffset (computer science)Solar energyScale (ratio)ElectricityEnvironmental economicsEconomicsNatural resource economicsEngineeringMeteorologyComputer sciencePhysicsGeographyElectrical engineeringCartography

Abstract

fetched live from OpenAlex

A key problem with solar energy is intermittency: solar generators produce only when the sun is shining, adding to social costs and requiring electricity system operators to reoptimize key decisions. We develop a method to quantify the economic value of large-scale renewable energy. We estimate the model for southeastern Arizona. Not accounting for offset carbon dioxide, we find social costs of $138.40 per megawatt hour for 20 percent solar generation, of which unforecastable intermittency accounts for $6.10 and intermittency overall for $46.00. With solar installation costs of $1.52 per watt and carbon dioxide social costs of $39.00 per ton, 20 percent solar would be welfare neutral.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.047
GPT teacher head0.252
Teacher spread0.205 · 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