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Record W85508888

Power electronics and control of a four inputs hybrid power system

2007· other· en· W85508888 on OpenAlexfundno aff
Tariq Iqbal, John E. Quaicoe

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2007
Typeother
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPower electronicsHybrid powerRenewable energyElectric power systemWind powerPower optimizerPower moduleElectrical engineeringEngineeringPower engineeringPower (physics)Power controlPower-flow studyMaximum power point trackingElectronicsConvertersHybrid systemAutomotive engineeringSwitched-mode power supplyComputer sciencePower factorVoltageInverter
DOInot available

Abstract

fetched live from OpenAlex

A hybrid power system consists of two or more power sources working in parallel. Such a system needs power electronics to extract maximum power and to control the flow of power from each renewable power source to the users load. We consider a small hybrid power system consisting of two wind turbines, a PV array and a pico-hydro system. A parallel combination of DC-DC converters connected between renewable energy sources and a common DC bus is used to control the power flow in the hybrid power system. In this paper we present a power electronic and control solution for such four inputs small hybrid power system with a common 48V DC bus. System power electronics design and proposed control strategies for each renewable power inputs are presented. Design and development progress of the proposed power electronics and control arrangement is included in the paper.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2007
Admission routes1
Has abstractyes

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