Comparison of ANN and P&O MPPT methods for PV applications under changing solar irradiation

Citation

Khanaki, Razieh and Marhaban, Mohammad Hamiruce and Mohd Radzi, Mohd Amran (2013) Comparison of ANN and P&O MPPT methods for PV applications under changing solar irradiation. In: IEEE Conference on Clean Energy and Technology (CEAT 2013), 18-20 Nov. 2013 , Langkawi, Kedah, Malaysia. (pp. 287-292).

Abstract

This paper presents an artificial neural network (ANN) maximum power point tracking (MPPT) method which is fast and precise in finding and tracking the maximum power point (MPP) in photovoltaic (PV) applications, under rapidly changing of solar irradiation, and is stable under slowly changing of solar irradiation. ANN and P&O MPPT algorithms, and other components of the MPPT control system which are PV module and DC-DC boost converter, are simulated in MATLABSimulink, and their performances under rapidly and slowly changing of solar irradiation are compared as well. Simulation results show that ANN method has very fast and more precise response under fast changes of solar irradiation. In addition, this method performs with less power oscillation under constant or slow changes of solar irradiation.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/CEAT.2013.6775642
Publisher:	IEEE
Keywords:	Maximum power point tracking (MPPT); Artificial neural network (ANN); Perturbation and observation (P&O); Photovoltaic (PV)
Depositing User:	Azian Edawati Zakaria
Date Deposited:	03 Dec 2015 07:59
Last Modified:	28 Jan 2016 02:39
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/CEAT.2013.6775642
URI:	http://psasir.upm.edu.my/id/eprint/41481
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