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Design of an off-grid photovoltaic power generation system for a household in Xinjiang region

2024· article· en· W4405271152 on OpenAlexaboutno aff
Ru Yang, Yihang Lu, Yaolin Lou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemGridGrid-connected photovoltaic power systemPower gridElectricity generationPower (physics)Rooftop photovoltaic power stationComputer scienceElectrical engineeringEnvironmental scienceMaximum power point trackingEngineeringGeographyVoltagePhysics

Abstract

fetched live from OpenAlex

This project presents the design of an off-grid photovoltaic power supply system for a user in the Xinjiang region. Based on local electricity consumption habits and the number of household appliances, the daily electricity consumption of the user is estimated at $9.824 \mathbf{k W h}$. The system utilizes five CS7N-670MS photovoltaic modules from Canadian Solar, connected in a 1 series $\times 5$ parallel configuration, with a module spacing of 3.172 m. The battery system employs AcmeG 12V 200 batteries from Narada, connected in a 4 series $\times 2$ parallel configuration. The selected inverter model is Sun2000-10kTL-M1 200vac. PVsyst software simulation indicates that with a system tilt angle of 60°, the power generation over the project's 25 -year lifespan is $109,434 \text{kWh}$. This translates to savings of $33,103.785 \text{kg}$ of standard coal equivalent, and reductions in emissions of 601.996 kg of sulfur dioxide, $96,750.599 \text{kg}$ of carbon dioxide, and 189.102 kg of nitrogen oxides. This project provides a theoretical reference for the design of household off-grid photovoltaic power generation systems.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.625
Threshold uncertainty score0.836

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 head0.044
GPT teacher head0.241
Teacher spread0.196 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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