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Record W4386527527 · doi:10.1615/978-1-56700-525-7.76

Chapter 1. Renewable Energy Storage: Too Many Options, Not Enough Time?

2022· book-chapter· en· W4386527527 on OpenAlexaff
Graham T. Reader

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRenewable energyComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The central, if not only, strategy to end anthropogenic climate change is the complete replacement of the use of natural fossil fuels, as soon as possible, by energy generated preferably from renewable and sustainable sources.This is a more significant challenge than often imagined since fossil fuels account for more than 63% of electrical generation globally, and at least 84% of global energy consumption.Two decades ago the fossil fuel share of electricity production was 64.8% and 86.1% of energy consumption [1].These slight decreases have been described as a slump in use, while the share of global energy consumption from renewable energies use has increased over the past decade from 16.4 to 17.1%, often described as a rapid or an exponential rise (see, e.g., [2,3]).These are likely well-intentioned narratives, but they could create notions and expectations that the transition away from fossil fuel usage will be simple, which is, unfortunately, misleading.The favored replacements for fossil fuels are renewable energy sources, especially solar and wind, but the variability, seasonality, geographic location, and intermittency of the sources present issues that must be overcome.Yet, there will be times when the energy generated by these sources exceeds consumer demand.If, during such times of overgeneration, the excess energy could somehow be stored to produce continuous, levelized, demand-supply attributes, then it should be possible for the adoption of renewable energy sources to be accelerated.Additionally, adequate energy storage could lessen the huge costs associated with the rapid installation of universal electrical grid systems and increasing larger solar and wind energy conversion farms.Smil's authoritative history of energy transitions shows that they are far from being instant and are driven largely by availability, affordability, and consumer acceptance [4].However, to these transition drivers must now be added the concerns associated with anthropogenic climate change.Increases in greenhouse gas (GHG) emissions since the 18th century start of the Age of Fossil Fuels have been connected to the rising global terrestrial and oceanic surface temperatures, particularly by sophisticated climate models.These models forecast that

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.739
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1280.001

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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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