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Record W2523107619 · doi:10.3390/en9090760

Investigation of Energy and Environmental Potentials of a Renewable Trigeneration System in a Residential Application

2016· article· en· W2523107619 on OpenAlexafffundabout
Eun-Chul Kang, Euy-Joon Lee, Mohamed Ghorab, Libing Yang, Evgueniy Entchev, Kwang-Seob Lee, Lyu Nam-Jin

Bibliographic record

VenueEnergies · 2016
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNatural Resources Canada
FundersNatural Resources CanadaMinistry of Land, Infrastructure and Transport
KeywordsTRNSYSRenewable energyChillerEnvironmental sciencePhotovoltaic systemElectricityHeat pumpBoiler (water heating)Chilled waterWaste managementEnvironmental engineeringAutomotive engineeringEngineeringHeat exchangerWater coolingThermalMeteorologyElectrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Micro polygeneration utilizing renewable energy is a suitable approach to reduce energy consumption and carbon emission by offering high-efficiency performance, offsetting the need for centrally-generated grid electricity and avoiding transmission/distribution losses associated with it. This paper investigates the energy and environmental potential of a renewable trigeneration system in a residential application under Incheon (Korea) and Ottawa (Canada) weather conditions. The trigeneration system consists of a ground-to-air heat exchanger (GAHX), photovoltaic thermal (PVT) panels and an air-to-water heat pump (AWHP). The study is performed by simulations in TRNSYS (Version 17.02) environment. The performance of the trigeneration system is compared to a reference conventional system that utilizes a boiler for space and domestic hot water heating and a chiller for space cooling. Simulation results showed substantial annual primary energy savings from the renewable trigeneration system in comparison to the reference system—45% for Incheon and 42% for Ottawa. The CO2eq emission reduction from the renewable trigeneration system is also significant, standing at 43% for Incheon and 82% for Ottawa. Furthermore, trigeneration systems’ capability to generate electricity and thermal energy at the point of use is considered as an attractive option for inclusion in the future smart energy network applications.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.200

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 head0.004
GPT teacher head0.154
Teacher spread0.150 · 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 designBench or experimental
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 routes3
Has abstractyes

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