Hunter - Prey Optimization for MPPT of Single Stage Grid Connected PV System with Novel Multilevel Inverter Topology Under Partial Shading Conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".