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Record W4404622558 · doi:10.1016/j.solcom.2024.100096

The macro view of solar policy: The case for supporting utility-scale power

2024· article· en· W4404622558 on OpenAlexaff
Anil Hira

Bibliographic record

VenueSolar Compass · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMacroScale (ratio)Solar powerMacro levelEnvironmental economicsPower (physics)EconomicsComputer scienceEconomic systemGeographyPhysicsCartographyThermodynamics

Abstract

fetched live from OpenAlex

• Solar costs have come down drastically over the last decade. • Yet, solar power still provides less than 5% of electricity generation globally. • Policy is fragmented among promoting utility-scale, commercial and residential solar. • Utility-scale is the only way to provide significant solar power and is the most efficient. • Utility-scale power requires increases in transmission capacity and integration of electricity markets. New solar energy generation is drastically needed as a source of clean electricity as the U.S. and the globe make the transition away from fossil fuels. Yet, even as solar costs have dramatically declined, solar sources still provide less than 5% of global electricity. We examine issues in solar policy leading to this low adoption rate. Examining the variables of cost, baseload power and intermittency, and land use, we evaluate the tradeoffs among policy support for utility-scale, commercial and residential solar systems. We argue that utility-scale solar power makes far more sense if there is adequate grid integration, so that such installations can be placed in locations that minimize land use tradeoffs. By focusing policy support on a few large solar installations, governments can vastly increase the solar contribution to electricity generation.

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.

How this classification was reachedexpand

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.274
Teacher spread0.259 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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