MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic

Authors

  • 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

DOI:

https://doi.org/10.21776/jeeccis.v8i2.259

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

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Published

2014-12-11

How to Cite

[1]
G. Wibisono, S. H. Pramono, and M. A. Muslim, “MPPT Menggunakan Metode Hibrid JST dan Algoritma Genetika Untuk Sistem Photovoltaic”, jeeccis, vol. 8, no. 2, pp. pp.181–186, Dec. 2014.

Issue

Vol. 8 No. 2 (2014)

Section

Articles