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Record W2939470824 · doi:10.1002/ep.13239

Techno‐economic feasibility of building attached photovoltaic systems for the various climatic conditions of Iran

2019· article· en· W2939470824 on OpenAlexaff
Mohammad Sadjad Karimi, Farivar Fazelpour, Marc A. Rosen, Mehrzad Shams

Bibliographic record

VenueEnvironmental Progress & Sustainable Energy · 2019
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPhotovoltaic systemPayback periodRoofElectricityGreenhouse gasEnvironmental scienceSolar energyElectricity systemBuilding envelopeElectricity generationArchitectural engineeringEnvironmental engineeringCivil engineeringMeteorologyEngineeringGeographyProduction (economics)EconomicsElectrical engineeringEcology

Abstract

fetched live from OpenAlex

Abstract The integration of solar energy systems into buildings via photovoltaic (PV) and other technologies can curb the amount of greenhouse gas emissions produced by buildings. However, the performance of solar energy systems is highly dependent on climatic and economic conditions. In this regard, the techno‐economic feasibility of building attached PV systems are studied for three scenarios considering three cities of Iran namely Tehran, Tabriz, and Kish Island, which have different climatic conditions. The result shows that the PV systems can annually meet 4.5–20% of the electricity needs for Tehran, 3.0–13% for Tabriz and 2.0–11.5% for Kish Island. Moreover, roof mounted PV systems were found to be a better alternative to envelope attached systems in technical and economic terms. The payback period for the solar energy systems was found to be between 8.7 and 14.3 years for Tehran, 14.2 and 22.6 years for Tabriz, and 11.6 and 21.1 for Kish Island.

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 score0.027
Threshold uncertainty score0.603

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 head0.219
Teacher spread0.212 · 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

Citations14
Published2019
Admission routes1
Has abstractyes

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