MétaCan
Menu
Back to cohort
Record W2100836559 · doi:10.1109/pesc.2004.1355417

A modified adaptive hill climbing MPPT method for photovoltaic power systems

2004· article· en· W2100836559 on OpenAlexaff
Weidong Xiao, W.G. Dunford

Bibliographic record

Venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551) · 2004
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaximum power point trackingHill climbingPhotovoltaic systemMaximum power principleControl theory (sociology)Computer sciencePower (physics)Steady state (chemistry)ClimbingEngineeringControl (management)Artificial intelligenceElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver maximum available power. In this paper, a modified adaptive hill climbing (MAHC) MPPT method is introduced. It can be treated as an extension of the traditional hill climbing algorithm. The simulation and experimental results show that the proposed MPPT control can avoid tracking deviation and result in improved performance in both dynamic response and steady-state.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.023
GPT teacher head0.283
Teacher spread0.259 · 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
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

Citations725
Published2004
Admission routes1
Has abstractyes

Explore more

Same venue2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551)Same topicPhotovoltaic System Optimization TechniquesFrench-language works237,207