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Record W6968022627 · doi:10.5281/zenodo.1283814

A Prospective Study On The Geothermal Potential In The Eu

2013· article· en· W6968022627 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2013
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsGeothermal gradientRenewable energyElectricity generationGeothermal powerElectricityGeothermal energyResource (disambiguation)

Abstract

fetched live from OpenAlex

Geothermal power generation has its roots in Europe, where the first test in 1904 and the real beginning of power generation in 1913 took place in Italy. Since then, the development of geothermal technology has been slow but continuous. Since a decade, thanks to the optimisation of the new binary system technology, geothermal electricity can be produced using lower temperatures. Moreover, with Enhanced Geothermal Systems (EGS), a breakthrough technology proven since 2007, geothermal power can in theory be produced anywhere in Europe. According to the trajectories set out in the National Renewable Energy Action Plans (NREAPs) of the EU Member States, the capacity will grow from 0.9 GWe installed in 2013 to 1.4 GWe in 2020. The production of geothermal electricity in 2020 is planned to be 11 TWh. These are very conservative targets as the actual potential is much larger. Indeed, information about geothermal potential is not always available (no geological data below 2-3 km from previous exploration campaign for oil, gas etc.) or it is scattered in different<br> ministries, universities, national institutes, oil &amp; gas companies and various private entities.<br> For this reason many policy-makers are simply not aware they stand on a frequently untapped source of local renewable energy. And this is also why geothermal power is not always taken sufficiently into consideration in some NREAPs and other strategic documents<br> on the future electricity mix. The present GEOELEC study makes a first step to fill the existing gap. It provides an outlook of the potential by country; the resource assessment is the product of the integration and interpretation of existing data and a newly defined methodology building on Canadian, Australian, and American methodology. The geological potential (heat in place) for geothermal power has been translated to an economical potential, using a Levelised Cost of Energy (LCoE) value of less than 150 EUR/MWh for the 2030 scenario and less than 100 EUR/MWh for the 2050 scenario: The total geothermal electricity potential in the EU-28 is 21,2 TWh for the year 2020; In 2030 this amounts to 34 TWh or 1% of the projected total electricity production in the EU; Thanks to economies of scale, innovative drilling concepts and substantial cost reduction, the economic potential in the EU grows to approximately 2570 TWh in 2050 potentially covering as much as 50% of the projected electricity produced in the EU) and more than 4000 TWh including Iceland, Turkey and Switzerland.

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 categoriesScience and technology studies, 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score1.000

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.013

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 head0.025
GPT teacher head0.228
Teacher spread0.203 · 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
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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