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Record W4307551735 · doi:10.3390/en15217906

Energy Performance Evaluation of a Solar PVT Thermal Energy Storage System Based on Small Size Borefield

2022· article· en· W4307551735 on OpenAlexaboutno aff
Evangelos Sakellariou, Petros J. Axaopoulos, Bill Vaneck Bôt, Ioannis E. Sarris

Bibliographic record

VenueEnergies · 2022
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsTRNSYSThermal energy storageEnvironmental scienceRenewable energyEnergy storageHeat pumpSolar energyNuclear engineeringProcess engineeringMeteorologyThermalEngineeringElectrical engineeringMechanical engineeringGeographyPower (physics)ThermodynamicsPhysicsHeat exchanger

Abstract

fetched live from OpenAlex

In this study, a PVT-based solar-assisted ground source heat pump (SAGSHP) system with a small size borefield as the long-term heat storage component was energetically evaluated. The mathematical model of the system was formulated in TRNSYS and three cities with distinctive climates were chosen: Athens (Greece); Melbourne (Australia); and Ottawa (Canada). The parametric analyses were carried out for 10 years by varying the number of the PVT collectors and the size of the earth energy bank (EEB). The evaluation of the systems was made via two energy indicators, and the heat flow across the EEB was analyzed. The under-consideration system was found capable of establishing self-sufficiency as regards the energy consumption (renewable power fraction RPF > 1) for all locations. Namely, for Athens, any system with more than four PVT collectors, and for Melbourne, any system with more than eight PVTs was found with an RPF higher than 1, regardless of the EEB size. For Ottawa, self-sufficiency can be achieved with PVT arrays larger than 12 collectors for small EEBs, and with eight collectors for larger EEBs. The storage capacity was found to be an important parameter for the energy performance of the system. In particular, it was determined that, as the storage capacity enlarges the RPF and the seasonal performance factor (SPF) of the system improves, mainly due to the reduction of the electricity consumed by the heat pump and the auxiliary heating. Moreover, a larger storage capacity facilitates solar heat production by enlarging the available heat storage volume and by maintaining the EEB at relatively low temperatures.

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: Empirical
Teacher disagreement score0.101
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.017
GPT teacher head0.215
Teacher spread0.197 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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