PSO and ANN Based Hybrid MPPT Algorithm for Photovoltaic Array under Partial Shading Condition
DOI:
https://doi.org/10.18034/ei.v8i1.481Keywords:
Photovoltaic (PV), Maximum power point tracking (MPPT), Partial Shading Condition (PSC), Particle Swarm Optimization (PSO), Artificial neural network (ANN)Abstract
MPPT is an electronics device that extracts maximum available power from a PV module under varying environmental conditions. But most of the conventional MPPT methods fail to track maximum power under partial shading condition (PSC). Partial shading is the most common situation in PV power generation, which is caused if part of the series-connected strings is partially shaded. This situation leads to the multiple peaks in the P-V characteristics curve of the PV system. So stochastic search method, Particle Swarm Optimization (PSO), is used instead of the conventional methods to track maximum power under PSC. But the PSO method has the limitation of slow operation. So in this paper, a fast hybrid method is presented, which combines the PSO method with the ANN method. In this hybrid method, the ANN enables the existing PSO method to track MPP quickly by providing more accurate initial particle positions of the PSO algorithm.
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