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Record W3166647100 · doi:10.1109/tpel.2021.3089551

A Low-Cost Cell-Level Differential Power Processing CMOS IC for Single Junction Photovoltaic Cells

2021· article· en· W3166647100 on OpenAlexaff
Afshin Amoorezaei, S. Ali Khajehoddin, Nasrin Rezaei-Hosseinabadi, Kambiz Moez

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2021
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConvertersPhotovoltaic systemMaximum power point trackingElectronic engineeringElectrical engineeringCMOSEngineeringBuck converterVoltageLow voltagePower (physics)Computer sciencePhysicsInverter

Abstract

fetched live from OpenAlex

This article presents a cell-level differential power processing IC to maximize the power yield under partial shading and mismatch condition in series-connected single junction photovoltaic (PV) cells. A 3-MHz bidirectional buck-boost converter is employed to realize voltage equalization technique forcing the PV cells to constantly operate close to their maximum power points. A novel and simple low-power low-area analog control circuit is proposed to maintain the high system efficiency at low and high levels of mismatch by obviating the need for power hungry blocks such as analog to digital converters, digital to analog converters, op-amps, saw-tooth generator, and regulators. The voltage of adjacent PV cells is used to drive the high-side switches through bootstrap supplies eliminating the need for voltage regulators. The performance of the proposed IC, fabricated in 130 nm CMOS process, is validated through simulation and experimental results. The converter is capable of processing mismatch currents up to 4 A while the control circuitry consumes less than 40 mW and a system efficiency above 95% is achieved.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

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