Artificial Neural Network for Solar Photovoltaic System Modeling and Simulation

Cho Hnin Moh Moh Aung; Myint Thuzar

Title:
Artificial Neural Network for Solar Photovoltaic System Modeling and Simulation

Authors:
Myint Thuzar | Cho Hnin Moh Moh Aung

Cite This Article :

Myint Thuzar | Cho Hnin Moh Moh Aung "Artificial Neural Network for Solar Photovoltaic System Modeling and Simulation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5, August 2019, pp.2110-2114, URL: https://www.ijtsrd.com/papers/ijtsrd27867.pdf

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Abstract :
This paper presented neural network based maximum power point tracking on the design of photovoltaic power input to a DC-DC boot converter to the load. Simulink model of photovoltaic array tested the neural network with different temperature and irradiance for maximum power point of a photovoltaic system. DC-DC boot converter is used in load when an average output voltage is stable required which can be lower than the input voltage. At the end, the different temperature and irradiance of the data collected from the photovoltaic array system is used to train the neutral network and output efficiency of the designed DC-DC boot converter with MPPT control strategy is accepted the maximum power amount to show the result voltage, current and power output for each different have been presented. And also demonstrated that the neural network based MPPT tracking require less time and more accurate results than the other algorithm based MPPT.

Keywords :
Neural Network; Maximum Power Point; Irradiance & Temperature; DC-DC Boot Converter

Publication Details:

Unique Identification Number : IJTSRD27867

Published In : Volume-3 | Issue-5, August 2019

Page Number(s) : 2110-2114

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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