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Record W2106797675 · doi:10.1109/pesc.2004.1355425

An improved perturbation and observation maximum power point tracking algorithm for PV arrays

2004· article· en· W2106797675 on OpenAlexaff
X. Liu, Luiz A. C. Lopes

Bibliographic record

Venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551) · 2004
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsPerturbation (astronomy)Control theory (sociology)Maximum power point trackingMaximum power principleAlgorithmComputer scienceMathematicsPower (physics)Photovoltaic systemEngineeringPhysicsControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

This paper discusses a new implementation of a perturbation and observation (P&O) maximum power point tracking (MPPT) algorithm that can mitigate/reduce the main drawbacks commonly related to the P&O method. This is achieved with peak current control, small perturbation values and sampling of instantaneous values, instead of averaged, to speed up the system response and reduce the oscillations around the maximum power point (MPP). The number of samples per switching cycle, type (synchronized/ unsynchronized) and ideal instant for sampling (maximum or minimum current) are investigated in order to obtain fast calculation of the direction of the next perturbation. Experimental results with the proposed control scheme implemented in a DSP are presented.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.259
Teacher spread0.242 · 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
GenreMethods

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

Citations250
Published2004
Admission routes1
Has abstractyes

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