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Record W2895212710 · doi:10.1002/ep.12939

Performance analysis of a photovoltaic/wind/diesel hybrid power generation system for domestic utilization in winnipeg, manitoba, canada

2018· article· en· W2895212710 on OpenAlexaffabout
Mahdieh Arabzadeh Saheli, Farivar Fazelpour, Nima Soltani, Marc A. Rosen

Bibliographic record

VenueEnvironmental Progress & Sustainable Energy · 2018
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDiesel generatorPhotovoltaic systemHybrid systemDiesel fuelHybrid powerBattery (electricity)Automotive engineeringEnvironmental scienceGreenhouse gasWind powerRenewable energyEngineeringPower (physics)MeteorologyElectrical engineeringComputer scienceGeography

Abstract

fetched live from OpenAlex

The development and modeling is reported of a photovoltaic (PV)/wind/diesel hybrid power generation system for a household in Winnipeg, Manitoba, Canada. For optimizing and determining the feasibility of the system, Homer simulation software is utilized. Various system configurations are investigated and comparisons are made using an optimization approach. For the Winnipeg location, the annual mean and the peak loads are 16 kWh/d and 1.9 kW, respectively. It is found that the hybrid system comprising 1 kW PV arrays, a 2 kW diesel generator, five batteries and a 2 kW converter with a total net present cost of $33,110 and a cost of energy of 0.444 $/kWh has the optimal configuration. The results obtained with Homer software demonstrate that a hybrid wind/PV/diesel/battery power generation system has the lowest cost and the highest efficiency of the systems considered. The system helps reduce emissions of pollutants and greenhouse gases. © 2018 American Institute of Chemical Engineers Environ Prog, 38: 548–562, 2019

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 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 score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.212
Teacher spread0.201 · 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

Citations43
Published2018
Admission routes2
Has abstractyes

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