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Hunter - Prey Optimization for MPPT of Single Stage Grid Connected PV System with Novel Multilevel Inverter Topology Under Partial Shading Conditions

2025· article· W7140491142 on OpenAlexaff
Suma M R, Ahmed K. Ali, B. Christyjuliet, G. Veeranna, Gulshan Dhasmana, V. Thirumani Thangam, N. Srinivas, Ajay Sudhir Bale, Kandi Bhanu Prakash

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsPhotovoltaic systemTopology (electrical circuits)ShadingMaximum power point trackingSingle stageControl theory (sociology)Grid

Abstract

fetched live from OpenAlex

New technologies of single stage grid integrated Photovoltaic (PV) systems are widely used worldwide. This technology is highly recommended for home applications where installed rooftop PV systems. Conventional inverters are creating problems of imposing high harmonics into utility grid. Hence, a novel five level single phase inverter topology is developed in this paper by utilizing only six numbers of power electronic switches. In order to establish a PV system, four arrays are considered in this paper where connected in parallel. At the same time, Partial Shading Conditions (PSCs) are imposing multiple peaks on PV characteristics which results failing of conventional Maximum Power Point Tracking (MPPT) methods. To avoid this issue, a novel optimization method namely Hunter - Prey Algorithm (HPA) is developed in this paper to identify exact location of maximum power point under PSCs. A hybrid control technique is implemented in this paper on proposed multilevel inverter for achieving multiple objectives including the operation of MPPT, regulating voltage at load bus, compensating reactive power at local bus connected to utility grid, and etc. Various responses of proposed HPA are compared with existing BOA, WOA, OOA and HOA. The Hardware - in the - Loop (HIL) configuration on OPAL-RT platform is utilized to present various responses in the results section.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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