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Record W2241763906 · doi:10.1109/epec.2015.7379960

Nonlinear maximum power point tracking controller for photovoltaic system

2015· article· en· W2241763906 on OpenAlexaff
Shamsodin Taheri, Hamed Taheri

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec en Outaouais
Fundersnot available
KeywordsMaximum power point trackingControl theory (sociology)Duty cyclePhotovoltaic systemNonlinear systemMaximum power principleController (irrigation)Transient (computer programming)MATLABComputer sciencePower (physics)Boost converterOperating pointEngineeringElectronic engineeringVoltagePhysicsInverterControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

This paper proposes a nonlinear maximum power point tracking (MPPT) controller for photovoltaic (PV) systems. The proposed MPPT technique is designed in conjunction with a Z-source dc-dc converter as an interface between the PV array and the load. To improve the system performance in transient regime as well as steady-state condition in both tracking and regulation, a nonlinear MPPT controller is designed. The scheme of the proposed nonlinear MPPT controller consists of the design of a nonlinear MPPT algorithm and a nonlinear controller for the duty cycle generation. The effectiveness of the proposed method is investigated via MATLAB simulation. In addition, the results are compared with the conventional perturb and observe (P&O) method. The simulation results highlight advantages of the proposed technique over the conventional P&O method in terms of an improved response in the transient state, an accurate tracking of the MPP as well as a significant reduction in oscillations around the maximum power point (MPP).

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.265
Teacher spread0.234 · 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 designBench or experimental
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

Citations6
Published2015
Admission routes1
Has abstractyes

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