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Record W7119496569 · doi:10.1098/rspa.2024.0841

A review of global tidal stream energy resources

2025· article· en· W7119496569 on OpenAlexaffabout

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2025
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsWilfrid Laurier University
FundersEngineering and Physical Sciences Research Council
KeywordsResource (disambiguation)ElectricityChinaTidal powerMains electricityEnergy (signal processing)Electricity generationResource use

Abstract

fetched live from OpenAlex

Abstract This review identifies 426 candidate sites with potentially suitable characteristics for tidal stream energy development, across 19 countries in Europe, the Americas, Asia and Australasia. The most common site assessment quantifies the theoretical resource, which is the maximum amount of total energy that can be extracted. The aggregated theoretical resource estimate, of 1000 TWh/year, from 262 sites (62% of those identified), across 6 countries, is equivalent to 115 GW of continuous annual power. A more informative, albeit less common assessment, considers technical, environmental and economic constraints on energy extraction. New data from UK assessments is presented that indicates relationships between the theoretical and this more practical level of energy extraction, which are used to derive practical levels of electricity generation at other sites across the world. Results indicate a quasi-practical resource of 110 TWh/year from 90 sites (20% of the candidate sites) across the UK, France, Canada, USA, China and New Zealand. When assessed against national/regional electricity production, the UK, Indonesia and New Zealand show the greatest potential to make national-scale electricity supply contributions, whilst France, Canada, USA and China exhibit lower, regional-scale impact potential. Resource estimation is highly sensitive to turbine/array design and practical constraints, and studies adopt a wide range. Consequently, reported P10 and P90 resource estimates can lie 40% above/below their P50 estimate, respectively. Recommendations are made to characterize this sensitivity of the resource to these drivers.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.852
Threshold uncertainty score0.268

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)0.0000.000

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 head0.005
GPT teacher head0.218
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

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 designTheoretical or conceptual
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
Published2025
Admission routes2
Has abstractyes

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