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Record W1976538970 · doi:10.1109/iecon.2012.6389107

Power management and control of a wind energy conversion system (WECS) with a fuzzy logic based maximum power point tracking (MPPT)

2012· article· en· W1976538970 on OpenAlex

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaximum power point trackingPower optimizerMaximum power principleWind powerControl theory (sociology)Power controlPower (physics)Battery (electricity)Computer sciencePower managementEngineeringElectrical engineeringPhotovoltaic systemControl (management)VoltageInverterPhysics

Abstract

fetched live from OpenAlex

This paper proposed a power management technique for a wind energy conversion system (WECS) with maximum power point tracking (MPPT). A two stage converter is proposed for the battery charger for energy storage purpose and for providing excess power to the “dump load” when there is surplus power in the battery and demanded by the load. The MPPT control algorithm used in the front-end converter is based on fuzzy logic control (FLC) technique. By monitoring the generator output power, the DC-link power and the load power, the proposed power management scheme is able to deliver maximum power from the wind and to control the power extracted from the wind when maximum power is not required from the load side. Simulation results will be given to highlight the merits of the proposed work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.881

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 head0.005
GPT teacher head0.165
Teacher spread0.161 · 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

Quick stats

Citations6
Published2012
Admission routes1
Has abstractyes

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