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Record W2036452567 · doi:10.1016/j.egypro.2012.11.120

The Influence of Energy Conservation on the Performance of Solar Thermal Systems – A Cold Country Case Study

2012· article· en· W2036452567 on OpenAlexafffundabout
Jörgen Wallin, Diane Bastien, Joachim Claesson

Bibliographic record

VenueEnergy Procedia · 2012
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesConcordia UniversityFonds de recherche du Québec – Nature et technologiesEuropean Commission
KeywordsEnergy conservationThermalEnvironmental scienceSolar energyEnvironmental economicsEngineering physicsNatural resource economicsEngineeringPhysicsMeteorologyEconomicsElectrical engineering

Abstract

fetched live from OpenAlex

The European Union has set a goal that the energy use in the built environment shall be reduced by 41% to the year 2050 compared to 2005-2006. This could introduce new opportunities for solar thermal systems in cold countries. In such countries, like Sweden and Canada, the economy in solar thermal collector installation projects is often spoiled by the fact that most of heating energy demand of the building occurs during periods when the available solar energy is low. The present paper investigates the performance of solar thermal systems subjected to different quota between space heating and domestic hot water demand (DHW). This study investigates the performance of a solar thermal system integrated to four different buildings with varying heating loads in two different locations, Sweden and Canada. Models of single family houses are created which are able to simulate the total heating demand with different heating demand profiles but the same DHW demand. Simulations are performed in TRNSYS, an advanced tool used to simulate transient systems. Results indicate that solar combisystems tend to generate more useful energy and therefore be more cost effective when installed in buildings with higher heating demands.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.271

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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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 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

Citations11
Published2012
Admission routes3
Has abstractyes

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