Evidence map›Paper›PMID 42218179›Full record

ArticleScientific reports2026

Dynamic analysis of GWO-Fuzzy MPPT technique applied to a SEPIC converter under partial shading conditions.

S Kamalakannan, M Marimuthu, P Ram Prakash

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

S KamalakannanDepartment of EEE, Saranathan College of Engineering, Tiruchirappalli, 620012, India. pskkamal96@gmail.com.
M MarimuthuDepartment of EEE, Saranathan College of Engineering, Tiruchirappalli, 620012, India.
P Ram PrakashDepartment of EEE, Saranathan College of Engineering, Tiruchirappalli, 620012, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Partial shading conditions (PSC) greatly reduce the performance of photovoltaic (PV) systems by adding many local maxima to the PV characteristics. This makes it very hard for traditional maximum power point tracking (MPPT) methods to work. To solve this problem, this research presents a comparative analysis of five hybrid MPPT algorithms: PO-Fuzzy, PSO-PO, GWO-Fuzzy, PSO-Fuzzy, and GWO-PSO, executed with a SEPIC converter functioning at 10 kHz with a 250 W PV module. We use MATLAB/Simulink to test how well these methods work in different partial shading situations. It examines the important elements, including PV voltage, PV power, output voltage, and output power. The results indicate that whereas PSO-PO and GWO-PSO enable faster initial convergence, the GWO-Fuzzy method achieves superior tracking accuracy, reduced steady-state oscillations, and reliable voltage control. The proposed GWO-Fuzzy approach ensures effective and reliable tracking of the global maximum power point (GMPP) with variations in sunlight intensity.

Indexed as

Fuzzy logic controllers (FLC)Global maximum power point (GMPP) trackingGrey wolf optimization (GWO)Hybrid optimization algorithmsMaximum power point tracking (MPPT)Partial shading conditions (PSC)Particle swarm optimization (PSO)Photovoltaic (PV) systemsPower electronicsSingle ended primary inductor converter (SEPIC)

Identifiers

PMID42218179
PMCPMC13457573

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.