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http://dx.doi.org/10.12673/jant.2020.24.4.291

Maximum Power Point Tracking of Photovoltaic using Improved Particle Swarm Optimization Algorithm  

Kim, Jae-Jung (Department of Energy IT, Gachon University)
Kim, Chang-Bok (Department of Energy IT, Gachon University)
Publication Information
Journal of Advanced Navigation Technology / v.24, no.4, 2020 , pp. 291-298 More about this Journal
Abstract
This study proposed a model that can track MPP faster than the existing MPPT algorithm using the particle swarm optimization algorithm (PSO). The proposed model highly sets the acceleration constants of gbest and pbest in the PSO algorithm to quickly track the MPP point and eliminates the power instability problem. In addition, this algorithm was re-executed by detecting the change in power of the solar panel according to the rapid change in solar radiation. As a result of the experiment, MPP time was 0.03 seconds and power was 131.65 for 691.5 W/m2, and MPP was tracked at higher power and speed than the existing P&O and INC algorithms. The proposed model can be applied when a change in the amount of power is detected by partial shading in a Photovoltaic power plant with Photovoltaic connected in parallel. In order to improve the MPPT algorithm, this study needs a comparative study on optimization algorithms such as moth flame optimization (MFO) and whale optimization algorithm (WOA).
Keywords
Photovoltaic; Maximum power point tracking; Perturbation and observation; Incremental conductance; Particle swarm optimization;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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