A Prospective Study On The Geothermal Potential In The Eu
Bibliographic record
Abstract
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 ministries, universities, national institutes, oil & gas companies and various private entities. 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 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".