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Record W4399140093 · doi:10.18280/mmep.110501

Reference Power Point Tracking Reference Power Point Tracking of the Inertial Storage System Connected to the Electrical Grid

2024· article· en· W4399140093 on OpenAlexvenueno aff
Saci Taraft, Djamila Rekioua, Abdelhak Djoudi, Seddik Bacha, Djamel Aouzellag

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsTracking (education)Power pointMaximum power point trackingPower (physics)Computer sciencePoint (geometry)GridElectrical engineeringEngineeringPhysicsMathematicsGeodesyGeographyVoltage

Abstract

fetched live from OpenAlex

In this paper, the operation of an inertial flywheel storage system based on the permanent magnet synchronous machine (PMSM) is presented.The contribution in this work lies in the optimization of the exchanged power between the storage system and the grid.The related speed reference is determinate from the desired power through a tracking algorithm known as reference power point tracking (RPPT).This one permit to achieve a desired grid-side power.That is ensured by a simple algorithm which needs only the measurements of grid-side power and reference power.This algorithm is robust because it doesn't depend to system parameters, and to an increased reliability.The problem of variable losses once several grid connected-storage systems are considered is then avoided.This will serve grid operator to adjust efficiently the grid frequency.The last point is the main advantage of the proposed method compared with others ones that use machine-side power measurements for speed reference synthetizing.The studied system is implemented under DSPACE type RTI1005.The rotation speed of the permanent magnet machine and the power exchanged between the electrical grid and the inertial storage system follow their reference with an error of 0.032% and 0.83% respectively.The simulation and experimental results presented show the effectiveness of the tracking algorithm.

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 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 score0.843
Threshold uncertainty score0.834

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.211
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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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