Cuckoo search algorithm and particle swarm optimization based maximum power point tracking techniques
Abstract
Increasing the efficiency of photovoltaic (PV) systems is a pressing issue, and several studies have focused on the Maximum Power Point Tracking (MPPT) techniques to extract the maximum PV output power. Many MPPT techniques have been discussed in the last decade, and optimization-based MPPT techniques have shown better performance than other MPPT techniques. In this study, two optimization techniques, the cuckoo search algorithm and particle swa9rm optimization with changing inertia weight techniques are discussed and applied to a PV system to track the maximum power point. The MSX-60 PV module and boost DC-DC converter are used in this paper to simulate and model the MPPT system using MATLAB/Simulink to show which technique has the best performance under various solar irradiation scenarios. In addition, different structures of PV arrays such as series-parallel, bridge link, and total cross-tied PV structures are simulated to analyze their effect on the efficiency of MPPT processes.
Keywords
Cuckoo search algorithm; DC–DC boost converter; Maximum power point trackers; Optimization algorithms; Photovoltaic systems; Particle swarm optimization; Renewable energy resources
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PDFDOI: http://doi.org/10.11591/ijeecs.v26.i2.pp605-616
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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).