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Record W4319459127 · doi:10.1109/tpel.2023.3243174

High Efficiency and Full MPPT Range Partial Power Processing PV Module-Integrated Converter

2023· article· en· W4319459127 on OpenAlex
Mohammad Daryaei, Morteza Esteki, S. Ali Khajehoddin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2023
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Alberta
FundersCanada First Research Excellence FundUniversity of Alberta
KeywordsMaximum power point trackingConvertersPhotovoltaic systemPower (physics)Maximum power principleElectronic engineeringPulse-width modulationControl theory (sociology)Electrical engineeringEngineeringComputer scienceVoltagePhysicsInverter

Abstract

fetched live from OpenAlex

To increase the energy yield of photovoltaic (PV) systems in the presence of module-level power mismatches, maximum power point tracking (MPPT) should be performed by converters at module level. Using module-level converters at the output of the PV panels adds a constant loss even when there is no power mismatch, which increases the overall system losses and compromises part of the energy yield improvement. To decrease this constant loss especially when there is no power mismatch, partial power processing (PPP) concept is used in this article to achieve a new high-frequency and high-efficiency module-integrated PV converter, which can achieve full range MPPT and maximum possible efficiency when there is no mismatch. To overcome the challenge of limited MPPT range for partial power converters, a special pulse density modulation technique is proposed, which preserves the merits of PPP and renders full range MPPT. A 220-W prototype converter is implemented to justify the converter principal of operation and analyses. The proposed converter reached 99.6%–96.5% efficiency for the power mismatches in the PV module ranging from 0% to 50% of the maximum module power generation capability, respectively. The efficiency drop is shown to be linear with power mismatch level without any abrupt reductions that is commonly observed in conventional PV module-integrated converters.

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)0.000
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 score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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