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Record W2751974380 · doi:10.1109/jphotov.2017.2746265

Submodule-Based Modeling and Simulation of a Series-Parallel Photovoltaic Array Under Mismatch Conditions

2017· article· en· W2751974380 on OpenAlexafffund
Xiangyun Qing, Hao Sun, Xiangsai Feng, Cheng-Huan Chung

Bibliographic record

VenueIEEE Journal of Photovoltaics · 2017
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsPhotovoltaic systemJacobian matrix and determinantComputer scienceSeries and parallel circuitsRobustness (evolution)Nonlinear systemVoltageDiodeSeries (stratigraphy)IrradianceControl theory (sociology)Electronic engineeringAlgorithmApplied mathematicsMathematicsMaterials scienceOptoelectronicsElectrical engineeringPhysicsOpticsEngineering

Abstract

fetched live from OpenAlex

This paper presents a simple and theoretically sound submodule-based model to simulate the characteristics of a photovoltaic (PV) array with a series-parallel configuration. The proposed model can describe the behavior of bypass diodes as well as the full PV array characteristics under varying irradiance and temperature conditions. Rather than using the nonlinear system of equations solved with a Jacobian matrix, separate equations are employed to model the submodule-based PV array and solved by an easy-to-implement bisection search method. Consequently, the output current of the PV array can be readily determined when its output voltage, the irradiance levels, and temperature values of all submodules are given. The robustness and calculation efficiency of the proposed computational method are analyzed. Some test examples allow us to exhibit the acceptable accuracy of the proposed model. Special attention of this work is paid to the simulation approach to evaluate the electrical mismatch losses in large-scale PV arrays with nonuniform aging after several years of field operation and exposure.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.299
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations37
Published2017
Admission routes2
Has abstractyes

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