Maximum Power Point Tracking of Solarex MSX PV Module System using FLC

2012 ◽  
Vol 2 (5) ◽  
pp. 21-31
Author(s):  
Alireza Rezaei
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pv Module ◽  
Power Point ◽  
Module System

Modeling of solar PV module and maximum power point tracking using ANFIS

2014 ◽  
Vol 33 ◽  
pp. 602-612 ◽  
Author(s):  
Ravinder Kumar Kharb ◽  
S.L. Shimi ◽  
S. Chatterji ◽  
Md. Fahim Ansari
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Solar Pv ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pv Module ◽  
Power Point

scholarly journals A STRUCTURE APPROACH FOR A PHOTOVOLTAIC STATION CONTROL BASED ON ADAPTIVE FUZZY AGENT

2017 ◽  
pp. 40-48
Author(s):  
I. A. Elzein ◽  
Yu. N. Petrenko
Keyword(s):  
Fuzzy Logic ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Pv Module ◽  
Power Point

The solar energy is directly converted into electrical energy by solar PV module. Each type of PV module has its own specific characteristic corresponding to the surrounding condition such as irradiation, and temperature and this makes the tracking of maximum power point (MPP) a complicated problem. To overcome this problem, many maximum power point tracking (MPPT) control algorithms have been presented. Fuzzy logic (FL) has been used for tracking the MPP of PV modules because it has the advantages of being robust, relatively simple to design and does not require the knowledge of an exact model where a mathematical model of the PV module, DC-DC converter, are used in the study of FL based MPPT algorithm. It is suggested to present this problem in the form of two-folds; first to identify the deviation of the power to maximum power point, and secondly, to control the voltage of the DC-DC converter corresponding to maximum power. In this paper, the first discussion approach will stress out the integration of model predictive control in maximum power point tracking MPPT and as progressing a second approach is identified as fuzzy logic controller FLC and perturb & Observe P&O algorithms are analyzed. All are interrelated to MPPT model for a photovoltaic module, PVM, to search for and generate the maximum power; in this case what’s called P-max. As per the first technique the focus is on the optimal duty ratio, D, for a series of multi diverse types of converters and load matching. The design of the MPPT for a stand-alone photovoltaic power generation system is applied where the system will consist of a solar array with nonlinear time varying characteristics, and a converter with appropriate filters. The integration of model predictive control will be addressed first in this paper. The second fold will implement an MPPT system that use the FLC and compare it with a classical MPPT P&O algorithm through the utilization of Simulink. The novel design in the FLC will be based on the use of asymmetrical membership functions to compensate for the asymmetrical P-V curve of solar panel.

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