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Record W2329086130 · doi:10.1109/icit.2014.6894988

Large-scale PV systems with energy storage utilizing high-gain DC/DC converters

2014· article· en· W2329086130 on OpenAlexaff
Hyuntae Choi, Mihai Ciobotaru, Vassilios G. Agelidis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotovoltaic systemConvertersTransient (computer programming)Energy storageGrid-connected photovoltaic power systemMaximum power point trackingComputer sciencePower (physics)Electric power systemElectronic engineeringInterconnectionVoltageElectrical engineeringEngineeringPhysicsTelecommunicationsInverter

Abstract

fetched live from OpenAlex

The trend associated with the ever increasing size of grid-connected photovoltaic (PV) systems necessitates PV system configurations with higher power rating power processing converters and interconnection at a higher voltage level at the point of common coupling (PCC). Moreover, the inherent intermittency of the solar irradiation greatly affects both transient- and steady-state operation of these ever larger PV systems. This paper proposes a solution dealing with challenges of the large-scale PV system. The paper introduces a multistring PV system configuration based on a high-gain DC/DC converter and energy storage system (ESS). The interleaved structure of the high-gain DC/DC converter can easily handle the challenges regarding the power rating of converters and the requirement of higher voltage at PCC. Moreover, the ESS suppresses the power fluctuation of PV arrays and balances the difference between generated PV power and peak load demand. The simulation results of proposed system are presented to validate the performance of transient and steady state.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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 designTheoretical or conceptual
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

Citations1
Published2014
Admission routes1
Has abstractyes

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