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Record W2895798748 · doi:10.31593/ijeat.441431

Design and analysis of PV fed SRM system

2018· article· en· W2895798748 on OpenAlexfundno aff
Serhat Berat Efe, Dilan DEMİR AKTAŞ

Bibliographic record

VenueInternational Journal of Energy Applications and Technologies · 2018
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsnot available
FundersCanadian Institute for Theoretical Astrophysics
KeywordsSwitched reluctance motorPhotovoltaic systemReliability (semiconductor)Renewable energyTorqueComputer scienceAutomotive engineeringFault (geology)Range (aeronautics)Induction motorControl theory (sociology)EngineeringPower (physics)Control (management)Electrical engineeringRotor (electric)Voltage

Abstract

fetched live from OpenAlex

Renewable energy sources supplied motor applications are being studied widely by researchers. As it is especially focused on design and control of such systems, studies on performance analysis approach is limited. It is vital to determine the operating behaviour of motor loads when they are supplied by limited energy sources like photovoltaic (PV) systems. According to this necessity, in this study, a switched reluctance motor (SRM) which is supplied by a PV system is analysed in terms of speed, current and torque data. Because of its advantages as it can be controlled over a wide range, its reliability and stability, SRM was used for analysis. Such data are observed in two cases, PV system irradiance change and fault conditions. System is designed as direct-fed, which is not include any storage unit. Therefore, any changes at supply system directly affect motor parameters. These effects and results are discussed by using the graphs that obtained from various points of system for both cases.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.219
Teacher spread0.211 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

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