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Record W1975481784 · doi:10.1504/12.47284

A case study of hybrid wind-solar power system for reduction of CO 2 emissions

2012· article· en· W1975481784 on OpenAlex
Ersin Akyüz, Zuhal Oktay, İbrahim Dinçer

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Global Warming · 2012
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPhotovoltaic systemEnvironmental scienceBattery (electricity)Hybrid systemAutomotive engineeringDiesel fuelHybrid powerWind powerTurbineMeteorologyEnvironmental engineeringPower (physics)EngineeringElectrical engineeringAerospace engineeringComputer science

Abstract

fetched live from OpenAlex

In this study, the solar radiation and wind data pertaining to Bigadic region are analyzed to assess the performance of a hybrid Photovoltaic–Wind–Diesel– Battery energy system. The average energy consumption of the system is about 20.33 kWh per day and 600 kWh per month, with a peak power demand of 2.4 kW. A 10 kW Wind Turbine and a 1 kWp PV energy system with 48 kW battery are installed. The emissions and energy costs are calculated and compared with the diesel-only and hybrid system. A break-even analysis is conducted for the hybrid system, which turned out to equal 1.44 km.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.529

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)0.0000.000

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 head0.022
GPT teacher head0.309
Teacher spread0.288 · 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