A Novel Comparative Analysis of Solar P&O, ANN-based MPPT Controller under Different Irradiance Condition

The depletion of fossil fuels and rising energy demand have increased the use of renewable energy. Among all Solar PVs, system-based electricity production is increased due to multiple advantages. In this paper a Solar PV system with an Artificial Neural Network (ANN)-based Maximum Power Point Trac...

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Bibliographic Details
Main Authors: Pavithra C, Dhayalan R, Anandha Kumar S, Dharshan Y, Haridharan R, Vijayadharshini M
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2024-01-01
Series:EAI Endorsed Transactions on Energy Web
Subjects:
Online Access:https://publications.eai.eu/index.php/ew/article/view/4942
Description
Summary:The depletion of fossil fuels and rising energy demand have increased the use of renewable energy. Among all Solar PVs, system-based electricity production is increased due to multiple advantages. In this paper a Solar PV system with an Artificial Neural Network (ANN)-based Maximum Power Point Tracking (MPPT) controller is developed. ANN has multiple advantages like stability, improved dynamic response, and fast and precise output. The System is modelled with a DC-DC boost converter with Perturb and Observe (P&O)-based MPPT controller which is operated in MATLAB-based Simulink model. Both the controller output is analyzed and compared, among these two controllers ANN has very fast and more precise output under dynamic conditions.
ISSN:2032-944X