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Record W7134517612

Improved Performance of Hybrid Photovoltaic-Trigeneration Systems Over Photovoltaic-Cogen Systems Including Effects of Battery Storage

2012· article· en· W7134517612 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCogenerationAbsorption refrigeratorHybrid systemGreenhouse gasWaste heatWork (physics)ChillerHybrid powerBattery (electricity)
DOInot available

Abstract

fetched live from OpenAlex

Recent work has proposed that hybridization of residential-scale cogeneration with roof-mounted solar PV (photovoltaic) arrays can increase the PV penetration level in ideal situations by a factor of five. In regions where there is a significant cooling load PV-cogen hybrid systems could be coupled to an absorption chiller to utilize waste heat from the cogen unit. In order to investigate realistic (non-ideal) loads that such a hybrid system would need to service, a new numerical simulation called PVTOM (PV-trigeneration optimization model) was created and coupled to the results of the established CHREM (Canadian Hybrid Residential End-Use Energy and Emissions Model). In this paper, PVTOM is applied to representative houses in select Canadian regions, which experience cooling loads, to assess the fuel utilization efficiency and reduction in greenhouse gas emissions from hybrid PV-cogen and trigen systems in comparison with conventional systems. Results of the optimization runs are provided and the efficacy of PV-cogen and PV-trigen systems is discussed. Both PV-trigen and PV-cogen systems have demonstrated to be more effective at reducing emissions when compared to the current combination of centralized power plants and household heating technologies in some regions. © 2012 Elsevier Ltd.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.194
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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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