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Record W7005826736

sEEnergies special report : Construction costs of new district heating networks in France

2022· article· en· W7005826736 on OpenAlexaboutno aff

Bibliographic record

VenueHogskolan Ihalmstad (Halmstad University) · 2022
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Marginal costHeating systemMarket penetrationService (business)Total costPenetration rateQuarter (Canadian coin)Distribution (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

This report aims to present the results of the work carried out within the sEEnergies project pertaining to estimating construction costs of new district heating networks in France. This project has followed a similar methodology to Heat Roadmap Europe when estimating the costs of district heating systems. Nonetheless, several improvements have been introduced to attain more realistic results. On the one hand, it has been carried out a detailed geographic analysis of two large Danish networks so the necessary pipe length can be better appraised. Moreover, both the distribution network and service pipes have been taken into consideration. On the other hand, pipe construction cost data from each country has been used to the maximum extent possible. This part of the project has only focused on the pipe network and has not taken into account other elements for the development of a district heating system, such as heat supply plants or the connections to the heat demands via a substation. The results for France show that the country has a significant potential for District Heating expansion. Approximately a quarter of the total heat demand (28%) could be supplied with a cost lower than 20 €/MWh and nearly half of the heat demand (47%) would be economically viable with a higher marginal cost of 30 €/MWh. Nonetheless, there is significant regional variation. For instance, for a marginal cost threshold of 20 €/MWh, Paris could cover nearly the entire heat demand and the other départements of the petite couronne de París, could reach penetration rates above 70%. On the contrary, the 12 least dense départements would not be able to deliver more than 10% of the heat demand, having the département of Vendée the lowest potential with merely 3%.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
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
Bibliometrics0.0010.002
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 head0.004
GPT teacher head0.159
Teacher spread0.155 · 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.

Study designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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