MétaCan
Menu
Back to cohort
Record W2025428229 · doi:10.1109/apec.2013.6520715

A transformer-less partial power boost converter for PV applications using a three-level switching cell

2013· article· en· W2025428229 on OpenAlexaff
Mohammed Agamy, Maja Harfman Todorovic, Ahmed Elasser, Somasundaram Essakiappan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCalifornia Energy Commission
KeywordsConvertersElectronic engineeringTransformerPhotovoltaic systemElectrical engineeringComputer scienceSwitched-mode power supplyBoost converterPower electronicsVoltagePower (physics)Topology (electrical circuits)Engineering

Abstract

fetched live from OpenAlex

Photovoltaic architectures with distributed power electronics provide many advantages in terms of energy yield as well as system level optimization. As the power level of the solar farm increases it becomes more beneficial to increase the dc collection network voltage, which requires the use of power devices with higher voltage ratings, and thus making the design of efficient, low cost, distributed power converters more challenging. In this paper a simple partial power converter topology is proposed. The topology is implemented using a three-level switching cell, which allows the use of semi-conductor devices with lower voltage rating; thus improving design and performance and reducing converter cost. This makes the converters suitable for use for medium to high power applications where dc-link voltages of 600V~1kV may be needed without the need for high voltage devices. Converter operation and experimental results are presented for two partial power circuit variants using three-level switching cells.

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 categoriesInsufficient 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: Methods · Consensus signal: none
Teacher disagreement score0.926
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.262
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
GenreMethods

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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicPhotovoltaic System Optimization TechniquesFrench-language works237,207