DOIONLINE

DOIONLINE NO - IJASEAT-IRAJ-DOIONLINE-19535

Publish In
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT
Journal Home
Volume Issue
Issue
Volume-11,Issue-1  ( Jan, 2023 )
Paper Title
Performance Analysis of Perturb & Observe, Incremental Conductance, and Neural Network MPPT for 2.5 KW Solar PV System
Author Name
Praveen Kamat, Anant Naik
Affilition
Pages
75-83
Abstract
Fossil fuels are extensively used for generating electricity to supply the need for energy to the world population. Fossil fuel burning increases pollution and global warming. As the quantity of fossil fuels is reducing day by day at an alarming rate, there is a need to reduce the use of fossil fuels and use alternate and renewable sources of energy. The world is using solar energy as one of the alternate sources of energy; the most common is the Solar PV system linked to the grid. Solar PV panel produces output voltage and current which depends on solar radiations, cell temperature, etc. and it has only one point on its I-V characteristics where it can supply maximum power, hence the solar PV panel should be operated at this point called MPP to extract maximum power from a solar panel at all times. In this article Perturb & Observe, Incremental Conducting & Neural network MPPT methods are simulated in SIMULINK for a 2500 Wp solar PV system and their performance is analysed. Keywords - MPPT, Solar PV, DC-DC boost converter, Artificial Neural Network, Perturb & Observe, Incremental Conductance
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