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Record W2342188981 · doi:10.3390/en9040291

Study on the System Design of a Solar Assisted Ground Heat Pump System Using Dynamic Simulation

2016· article· en· W2342188981 on OpenAlexaboutno aff
Min Yu, Yujin Nam, Youngdong Yu, Janghoo Seo

Bibliographic record

VenueEnergies · 2016
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTRNSYSHeat pumpThermal energy storageCoefficient of performanceEnvironmental scienceStorage tankThermalNuclear engineeringSystems designDynamic simulationSolar energyProcess engineeringEngineeringMeteorologyMechanical engineeringSimulationThermodynamicsHeat exchangerElectrical engineering

Abstract

fetched live from OpenAlex

Recently, the use of hybrid systems using multiple heat sources in buildings to ensure a stable energy supply and improve the system performance has gained attention. Among them, a heat pump system using both solar and ground heat was developed and various system configurations have been introduced. However, establishing a suitable design method for the solar-assisted ground heat pump (SAGHP) system including a thermal storage tank is complicated and there are few quantitative studies on the detailed system configurations. Therefore, this study developed three SAGHP system design methods considering the design factors focused on the thermal storage tank. Using dynamic energy simulation code (TRNSYS 17), individual performance analysis models were developed and long-term quantitative analysis was carried out to suggest optimum design and operation methods. As a result, it was found that SYSTEM 2 which is a hybrid system with heat storage tank for only a solar system showed the highest average heat source temperature of 14.81 °C, which is about 11 °C higher than minimum temperature in SYSTEM 3. Furthermore, the best coefficient of performance (COP) values of heat pump and system were 5.23 and 4.32 in SYSYEM 2, using high and stable solar heat from a thermal storage tank. Moreover, this paper considered five different geographical and climatic locations and the SAGHP system worked efficiently in having high solar radiation and cool climate zones and the system COP was 4.51 in the case of Winnipeg (Canada) where the highest heating demand is required.

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 score0.042
Threshold uncertainty score0.571

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 head0.050
GPT teacher head0.271
Teacher spread0.221 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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