Soft Computing Approaches for Maximum Power Point Tracking of Solar PV System

S. Radhika; Vijaya Margaret

doi:10.15866/iree.v18i6.23759

Soft Computing Approaches for Maximum Power Point Tracking of Solar PV System

S. Radhika^(1*), Vijaya Margaret⁽²⁾

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/iree.v18i6.23759

Abstract

Solar power changes according to irradiance and temperature in a day. A Maximum Power Point Tracking (MPPT) algorithm is actually necessary to obtain the maximum power from the photovoltaic (PV) arrangement. In this paper, in order to optimize power and improve the efficiency of PV module with regulated output voltage, soft computing MPPT techniques, flying squirrel search optimization and artificial bee colony methods are implemented on cascaded double voltage lift boost converter. The PV module is subjected to both with and without constraints to analyze the performance of the DC/DC converter, and the comparative outcomes are evaluated for resistive and different types of battery loads at various temperature conditions in MATLAB/Simulink platform. The optimized power is achieved by using artificial bee colony technique with less ripple in the output waveforms at constant 25 °C temperature irrespective of the changes in irradiation with the battery load and this can be used for charging of the battery system.
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Keywords

Photovoltaic System; Maximum Power Point Tracking Technique; Artificial Bee Colony Optimization; Cascaded DC/DC Converter; Flying Squirrel Search Optimization

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