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Record W3117721069 · doi:10.18280/jesa.530602

Impact of Polyphase Induction Motor on Photovoltaic Water Pumping System

2020· article· en· W3117721069 on OpenAlexvenueno aff
Koussaila Iffouzar, Khaldi Lyes, Kamal Himour, Abdelhakim Deboucha, Kaci Ghedamsi

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2020
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsPhotovoltaic systemControl theory (sociology)InverterInduction motorComputer scienceInduction generatorEngineeringMaximum power point trackingVoltageElectrical engineering

Abstract

fetched live from OpenAlex

An improved dynamic behavior of water pumping system is presented in this paper. The system consists of a seven-phase induction motor powered by a photovoltaic generator (PVG) and a battery bank, via two static converters controlled independently. A boost converter based on fuzzy logic controller is utilized to adapt the voltage of the photovoltaic generator in order to extract maximum power. A three levels neutral point clamped inverter (NPC) is introduced to attain a low voltage harmonic distortion in the system. In addition, an improved direct field oriented control with minimizing non-sequential currents for the seven-phase induction motor using fuzzy logic filter is implemented. To verify and validate the proposed system, an optimal operating point is chosen to locate the dynamic and static operating limits of the system. Moreover, the proposed system is simulated and analyzed. The minimization of the non-sequential currents component induces a quality energy improvement with minimizing of the Joule losses, which increase the system efficiency. The use of the seven-phase machine brings a degree of additional freedom to the system, its tolerance to faults is a capital issue for the isolated places.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.271
Teacher spread0.243 · 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
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

Citations2
Published2020
Admission routes1
Has abstractyes

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