Comparison of Maximum Power Point Tracking Methods Using Metaheuristic Optimization Algorithms for Photovoltaic Systems

Year 2021, Volume: 25 Issue: 4, 1075 - 1085, 30.08.2021

Necati Bilgin , İrfan Yazici

https://doi.org/10.16984/saufenbilder.936254

Cited By: 1

Abstract

The maximum power value that can be obtained from photovoltaic systems can change continuously due to environmental conditions such as temperature, sunlight and partial shading. Direct current-direct current (DC-DC) converters and maximum power point tracking (MPPT) algorithms are required, especially in cases of partial shading, in order for the photovoltaic systems to operate at the maximum power point, that is, to draw the maximum possible power value from the system. In this study, simulation studies has been carried out for two different partially shaded scenarios using the boost-type DC-DC converter and MPPT algorithm in the PV array consisting of 3 panels connected in series. In the simulation studies, the output powers obtained by the application of particle swarm optimization, cuckoo optimization, bat optimization and firefly optimization techniques as MPPT algorithm has been compared. In the scenarios examined, the firefly optimization algorithm reached the maximum power point faster, and it has been observed that the firefly optimization method obtained the highest average power at the end of the simulation periods.

Keywords

Photovoltaic system, partially shaded condition, MPPT, optimization algorithms, DC-DC converter

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