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Record W2124937476 · doi:10.1109/tpwrs.2007.901482

Generalized Estimation of Average Displaced Emissions by Wind Generation

2007· article· en· W2124937476 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 · 2007
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsRenewable energyWind powerEnvironmental economicsElectricity generationElectric power systemGreenhouse gasWork (physics)EstimationEngineeringEnvironmental scienceComputer sciencePower (physics)EconomicsSystems engineeringElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a generalized approach for the estimation of average displaced or avoided system emissions by intermittent renewable sources such as wind. The quantification of the environmental benefits of renewable energy projects is of utmost importance for: 1) the creation and trading of certified emission reductions or credits and 2) the design of green energy government policies that recognize the contribution of renewable energy for the reduction of national/regional carbon emissions. The proposed approach is based on the correlation factor between time-evolution of system marginal emissions and wind power generation. Results show that average displaced emissions by wind generation can be estimated once typical power system dispatch data and regional wind generation is available, thus circumventing the use of proprietary power dispatch models. The main objective of this work is to contribute towards the development of simplified methodologies that will facilitate the assessment of renewable energy projects in a variety of regulatory and regional settings.

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 score0.938
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
Bibliometrics0.0000.001
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 head0.221
Teacher spread0.213 · 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