Open AccessESTIMATION OF PV MODULE PARAMETERS USING GENERALIZED HOPFIELD NEURAL NETWORK
Author(s) -
R. Dharmarajan,
Rajeswari Ramachandran
Publication year - 2019
Publication title -
international research journal of multidisciplinary technovation
Language(s) - English
Resource type - Journals
ISSN - 2582-1040
DOI - 10.34256/irjmt1933
Subject(s) - photovoltaic system , equivalent series resistance , saturation current , artificial neural network , control theory (sociology) , shunt (medical) , computer science , optimization algorithm , environmental science , electronic engineering , engineering , mathematics , voltage , mathematical optimization , artificial intelligence , electrical engineering , medicine , control (management) , cardiology
The estimation of solar photovoltaic (PV) system with help of electrical model parameters, suchas photon generated current, the diode saturation current, series resistance, shunt resistance, anddiode ideality factor, are desirable to predict the real performance characteristics of solar PVunder varying environmental conditions. Finally, performance indices, such as PV characteristicscurve are estimated for the various solar PV panels using GHNN optimization technique.