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Record W7010446678

Hydraulic Rock Energy Storage for Utility Scale Wind Farm

2020· report· en· W7010446678 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2020
Typereport
Languageen
Field
Topic
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRenewable energyPumped-storage hydroelectricityIntermittent energy sourceEnergy storageWind powerEnergy (signal processing)Scale (ratio)GridGrid energy storage
DOInot available

Abstract

fetched live from OpenAlex

It is a known fact that renewables suffer from intermittency. This causes fluctuating energy generation which forces grid operators to encounter the problem of unbalanced power and frequency disturbances. Energy storage is always necessary if a high percentage of renewable energy sources are used. Therefore, the current study is quite significant as it introduces a new large-scale storage technique that happens to be sustainable in many ways and also encouraging as it forms an impressive combination of utility-scale renewable energy generation and energy storage. The ability to store power on a large scale will be an essential feature of any sustainable and reliable energy system. This can be accomplished by storing the energy in a local storage system with sufficient capacity. The Hydraulic Rock energy storage system is the solution to this ambitious level of self-sufficiency as it relies primarily on local resources and has an efficiency of over 80%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.002

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 head0.285
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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