MétaCan
Menu
Back to cohort
Record W4255404477 · doi:10.24018/ejeng.2020.5.12.2295

Optimal Sizing of a PV System in Golpayegan, Iran Using Thermal Modeling-based Load Demand

2020· article· en· W4255404477 on OpenAlex

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

VenueEuropean Journal of Engineering and Technology Research · 2020
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhotovoltaic systemSizingAutomotive engineeringGrid-connected photovoltaic power systemEnvironmental scienceGridDiesel fuelLoad profileBattery (electricity)Solar irradianceComputer scienceEngineeringMaximum power point trackingElectrical engineeringPower (physics)MeteorologyElectricityVoltageInverter

Abstract

fetched live from OpenAlex

This paper introduces the design and analysis of a Photovoltaic (PV) system to supply the residential load of a house in Golpayegan, Iran. The paper’s procedure is the house's thermal modeling employing BEopt software to estimate the load data and then collect the primary meteorological data such as solar irradiance and temperature for the selected site. After these preliminary steps, system optimization for PV/grid and PV/diesel/battery models are developed using the HOMER software. The optimization found that the PV array required capacities are 5.17 kW and 6.19 kW, producing 9,346 kWh/yr and 11,196 kWh/yr for standalone and grid-connected PV systems, respectively. The results indicate that solar energy utilization is an attractive option for grid-connected and standalone PV systems, of which the net present costs (NPC) of each system are 12,180 US$, 40,618 US$, respectively. The system analyses show that adopting either a PV/grid or PV/diesel/battery system causes a reduction in not only dependency on fossil fuel but also in CO2 emission.

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)0.002
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 score0.080
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.251
Teacher spread0.203 · 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