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Record W2140392767 · doi:10.1109/ccece.2005.1556998

Utility interactive fuel cell inverter for distributed generation: design considerations and experimental result

2006· article· en· W2140392767 on OpenAlexaff
M.J. Khan, M. Tariq Iqbal, John E. Quaicoe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDistributed generationInverterInterfacingComputer scienceGridFieldbusPulse-width modulationElectronic engineeringElectrical engineeringVoltageEngineeringRenewable energyControl systemComputer hardware

Abstract

fetched live from OpenAlex

Distributed generation (DG) systems are potential solutions for efficient and economic integration of many non-conventional energy sources into the existing power grid. Among various alternative power sources, fuel cells are strong candidates for DG applications. Suitable interfacing of such resources into the DG network critically depends on design and performance of the power conversion stage. In this work, the design and experimental results of a utility interactive fuel cell inverter system for DG application are discussed. A series resonant DC-DC converter coupled with a sinusoidal pulse width modulated (SPWM) inverter is considered as the power stage. While connected to the grid, the inverter works in the current controlled mode. Stand-alone mode of operation is maintained through a voltage-controlled scheme. A DSP (TMS320F2812) based feedback control architecture and aspects of utilizing controller area network (CAN) fieldbus within the DG network are discussed. Compatibility with the existing DG standards, cost issues, and performance indices are analyzed with reference to experimental results. Control, communication, and challenges of integrating fuel cell systems into the distribution grid are also highlighted

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score0.316

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)0.0000.000

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 head0.018
GPT teacher head0.212
Teacher spread0.194 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations8
Published2006
Admission routes1
Has abstractyes

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