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Record W2182494905

Potential of decentralized heat pumps to improve the financial viability of a solar district heating system with seasonal thermal storage

2014· other· en· W2182494905 on OpenAlexaboutno aff
Mathilde M. Krebs, Humberto Jose Quintana, Michaël Kummert

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2014
Typeother
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsCapital costThermal energy storageSolar water heatingComponent (thermodynamics)Environmental scienceFraction (chemistry)Solar energyPhotovoltaic systemLife-cycle cost analysisEngineeringProcess engineeringEnvironmental economicsMeteorologyEnvironmental engineeringReliability engineeringEconomicsElectrical engineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper uses the Drake Landing Solar Community as a case study to assess the potential of including decentralized water-to-air heat pumps within a solar district heating system. A design exercise is performed using a component-based simulation program to assess the performance of different system configurations and design parameters, and a generic optimization tool to optimize the system life cycle cost. The selected economic parameters represent the current situation of the existing community in Alberta, Canada. The energy performance of the proposed configuration is assessed, as well as the life-cycle costs (capital and operating costs over 20 years). Different targets for solar fraction are assessed, and two types of solar collectors are compared (unglazed vs. glazed flat-plate collectors). The results show that decentralized heat pumps deliver life-cycle savings compared to a solar-only configuration for moderate solar fraction objectives. They also show that, with the selected assumptions and system configurations, the very high solar fraction achieved by the existing system cannot be matched.

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 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: none
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.191
Teacher spread0.187 · 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
Published2014
Admission routes1
Has abstractyes

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