A fast converging hybrid mppt algorithm based on abc and p&o techniques for a partially shaded pv system
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Date
2021-09
Profesor/a GuÃa
Facultad/escuela
Idioma
en_US
Journal Title
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Volume Title
Publisher
MDPI
Nombre de Curso
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Atribución/Reconocimiento 4.0 Internacional
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https://creativecommons.org/licenses/by/4.0/deed.es
Abstract
Among all the conventional maximum power point tracking (MPPT) techniques for a photovoltaic (PV) system that have been proposed, incremental conductance (INC) and perturb and observe (P&O) are the most popular because of their simplicity and ease of implementation. However, under partial shading conditions (PSCs), these MPPT algorithms fail to track the global maximum power point (GMPP) and instead converge into local maximum power points (LMPPs), resulting in considerable PV power loss. This paper presents a new hybrid MPPT technique combining the artificial bee colony (ABC) and P&O algorithms named ABC-P&O. The P&O technique is used to track the MPP under uniform irradiance, and only during irradiance variations is the ABC algorithm employed. The effectiveness of the proposed hybrid algorithm at tracking the GMPP, under both uniform and nonuniform irradiance conditions, was assessed by hardware-in-the-loop (HIL) tests employed by a dc–dc boost converter. Then, the ABC-P&O strategy was applied to obtain the voltage reference for the outer PI control loop, which provided the current reference to the discrete-time sliding-mode current control. The ABC-P&O algorithm has a reasonable computational cost, allowing the use of a commercial, low-priced digital signal controller (DSC) with outer voltage and inner current control loops. Many challenging tests validated that the proposed ABC-P&O technique converges fast to the GMPP with high efficiency and superior performance under different PSCs.
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Indexación: Scopus.
Keywords
Artificial bee colony, Hardware-in-the-loop testing, Maximum power point tracking, Partial shading conditions, Photovoltaic system
Citation
Mathematics Volume 9, Issue 18 September 2021 Article number 2228
DOI
10.3390/math9182228