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Record W2161587136 · doi:10.1109/pes.2011.6039163

Control of three phase grid-connected photovoltaic arrays with open loop maximum power point tracking

2011· article· en· W2161587136 on OpenAlexaff
Ahmed S. Khalifa, Ehab F. El‐Saadany

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaximum power point trackingPhotovoltaic systemPower optimizerMaximum power principleControl theory (sociology)Computer scienceCapacitorBoost converterInverterPower (physics)Controller (irrigation)VoltageElectronic engineeringEngineeringElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

This paper proposes a control technique for medium and large scale PV arrays connected to the power system grid. The array is interfaced to the grid through power electronic converters to change output voltages and currents from DC to AC quantities. A DC-DC boost converter is used to step up the output voltage of the array and extract maximum power under a given temperature and solar irradiation. A voltage source inverter under current control mode is connected to the DC converter through a DC link capacitor used to store power and act as a fixed DC bus for the inverter. A controller is used to regulate the capacitor voltage and keep it constant by balancing its input and output powers. The inverter is controlled in the rotating (dq) frame to inject AC power into the grid. An open loop maximum power point tracking (MPPT) technique is proposed to quickly locate the maximum power point (MPP) of the PV array under varying weather conditions. This technique is simple to implement and does not require periodic measurements of the array output power as in most closed loop MPPT techniques. MATLAB software was used to simulate the system to confirm the performance and effectiveness of the proposed technique.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.888
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.038
GPT teacher head0.261
Teacher spread0.224 · 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

Citations17
Published2011
Admission routes1
Has abstractyes

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