A Novel Adaptive Neural MPPT Algorithm for Photovoltaic System

Authors

  • S. A. Allahyari Mehriz Branch, Islamic Azad University, Mehriz, Iran
  • Nasser Taheri Electrical Engineering Department, Technical and Vocational University, Sabzevar, Iran
  • M. Zadehbagheri Yasouj Branch, Islamic Azad University, Kohgiloyeh & Bovirahmad Province, Yasouj, Iran
  • Z. Rahimkhani Sarvestan Branch, Islamic Azad University, Sarvestan, Iran

DOI:

https://doi.org/10.15282/ijame.15.3.2018.2.0417

Keywords:

Photovoltaic systems; adaptive neural networks; MPPT algorithm

Abstract

This paper presents a novel adaptive neural network (ANN) for maximum power point tracking (MPPT) in photovoltaic (PV) systems under variable working conditions. The ANN-based MPPT model includes two separate NNs for PV system identification and control. NNs are trained by using of a novel back propagation algorithm in pre/post control phases. Because of online optimal performance of NNs, the proposed method, not only overcome the common drawbacks of the conventional MPPT methods, but also gives a simple and a robust MPPT scheme. Simulation results, which carried on MATLAB, show that proposed controller is the most effective in comparison with conventional MPPT approaches.

IJAME Volume 15 Issue 3 Sept 2018

Downloads

Published

2018-10-05

How to Cite

[1]
S. A. Allahyari, N. Taheri, M. Zadehbagheri, and Z. Rahimkhani, “A Novel Adaptive Neural MPPT Algorithm for Photovoltaic System”, Int. J. Automot. Mech. Eng., vol. 15, no. 3, pp. 5421–5434, Oct. 2018.

Issue

Vol. 15 No. 3 (2018): July-September

Section

Articles