An evaluation of a medium-power grid-Integrated Solar Photovoltaic System MPPT Energy Capturing Capability Using ANN

Technologies centered around renewable energy are now feasible options for providing everyone with quick and dependable access to electricity. Solar energy, in which photovoltaic (PV) cells can convert directly into electricity, is one of the most efficient renewable energy sources. The sun irradiat...

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Bibliographic Details
Main Authors: Vijaychandra Joddumahanthi, Vedaprakash Kakinada, Vanajakshi Bammidi, Łukasz Knypiński
Format: Article
Language:English
Published: Polish Academy of Sciences 2025-07-01
Series:International Journal of Electronics and Telecommunications
Subjects:
Online Access:https://journals.pan.pl/Content/135756/24-4793-Joddumahanthi_sk.pdf
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Summary:Technologies centered around renewable energy are now feasible options for providing everyone with quick and dependable access to electricity. Solar energy, in which photovoltaic (PV) cells can convert directly into electricity, is one of the most efficient renewable energy sources. The sun irradiation and temperature are the two factors that affect how much power photo voltaic systems can produce. In order to increase power, maximum power point tracking techniques have been developed and applied to PV systems. The proposed model was trained on a total of 1000 datasets containing information on voltage, temperature, and sun irradiation. Training, validation, and testing are the three categories into which the data are divided. The Artificial Neural Network (ANN) model was compared with the classical method like the perturb and observe method (P&O).
ISSN:2081-8491
2300-1933