Open AccessCascaded Feed Forward Multilayer Neural Network based MPPT Controller for Improving the Performance of Photovoltaic System
Author(s) -
M Rupesh
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i10.5575
Subject(s) - photovoltaic system , maximum power point tracking , computer science , controller (irrigation) , matlab , control theory (sociology) , automotive engineering , engineering , control (management) , electrical engineering , artificial intelligence , voltage , inverter , agronomy , biology , operating system
This paper deals with the energy production of photovoltaic (PV) cells in different weather conditions. Today, photovoltaic generation plays an important role in generating electricity and satisfies the demand of the island's consumers. The power generation of the PV cell was completely dependent upon sunlight and temperature, but sunlight and temperature changed forever in nature. The many researchers are working on different MPPT technologies for a PV system. Conventional MPPT controllers cannot withstand a sudden change of weather conditions. The main aim of this article is to compare the various conventional and intelligent controller such as the GA, Fuzzy, KGMO, and CNFF for MPPT of the PV system. The proposed intelligent controller was developed and simulated by the MATLAB environment for MPPT in the PV system. In addition, the above results are evaluated and compared. Based on performance, the optimal smart controller has been recommended as MPPT of the PV system