Jurnal EECCIS
Vol 8, No 2 (2014)

MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic

Gunawan Wibisono (Program Magister Teknik Elektro Fakultas Teknik, Universitas Brawijaya)
Sholeh Hadi Pramono (Jurusan Teknik Elektro Fakultas Teknik Universitas Brawijaya)
Muhammad Aziz Muslim (Jurusan Teknik Elektro Fakultas Teknik Universitas Brawijaya)



Article Info

Publish Date
11 Dec 2014

Abstract

Maximum Power Point Tracking is a method to track power point of an energy source in order to generate maximum power. One of the MPPT method for photovoltaic system is fractional open voltage MPPT. In this paper the fractional open voltage MPPT is modified by using artificial neural network trained using genetic algorithm. Artificial neural networks are successfully trained by using genetic algorithm. The best mean squared error (MSE) value obtained is 0.000453. The network tested using test data, yielding average error = 0.00949509 and MSE = 0.00012814. The neural network-based MPPT can improve the fractional open voltage MPPT by 4.79%.Index Terms---Genetic Algorithm, MPPT, Neural Network, Photovoltaic

Copyrights © 2014






Journal Info

Abbrev

EECCIS

Publisher

Subject

Engineering

Description

EECCIS is a scientific journal published every six month by electrical Department faculty of Engineering Brawijaya University. The Journal itself is specialized, i.e. the topics of articles cover electrical power, electronics, control, telecommunication, informatics and system engineering. The ...