Modelling and simulation of MPPT techniques for solar photovoltaic system using genetic algorithm optimised fuzzy logic controller

2020 ◽  
Vol 16 (2) ◽  
pp. 174
Author(s):  
Afshan Ilyas ◽  
M. Rizwan Khan ◽  
Mohammad Ayyub
Author(s):  
Rakhi K ◽  
Ilango Karuppasamy ◽  
Manjula G Nair

The long established battery chargers are having many drawbacks such as prominent ripple charging current, less efficiency and bulky in size. To overcome these drawbacks of conventional battery charger, several charging circuits have been proposed and inevitability force to design a high-performance battery charger with small in size and improved efficiency. In this paper solar photovoltaic system based half-bridge series–parallel resonant converter (HBSPRC) charger is proposed for battery interface. The converter is designed to abolish low and high-frequency ripple currents and thus take full advantage of the life of secondary battery circuit. This is achieved by designing converter switches turn on at zero current and zero voltage with switching frequency greater than that of resonance frequency which leads to freewheeling diodes need not have very fast reverse-recovery characteristics. The performance of the power converters depends upon the control method adopted; in this work fuzzy logic controller is used for controlling the output voltage of HBSPRC. The fuzzy control scheme for the HBSPR converter has been designed and validated in hardware implementation of HBSPRC switching technique.  From the results, it is found that the proposed battery charging system which reduces the switching loss and voltage stress across the power switches which increases the efficiency of the converter.


2013 ◽  
Vol 23 (2) ◽  
pp. 145-167 ◽  
Author(s):  
Nadia Drir ◽  
Linda Barazane ◽  
Malik Loudini

This paper presents design and application of advanced control scheme which integrates fuzzy logic concepts and genetic algorithms to track the maximum power point in photovoltaic system. The parameters of adopted fuzzy logic controller are optimized using genetic algorithm with innovative tuning procedures. The synthesized genetic algorithm which optimizes fuzzy logic controller is implemented and tested to achieve a precise control of the maximum power point response of the photovoltaic generator. The performance of the adopted control strategy is examined through a series of simulation experiments which prove good tracking properties and fast response to changes of different meteorological conditions such as isolation or temperature.


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