Comparative analysis of MPPT controllers in a photovoltaic system - de Medeiros Confessor, Sâmya Lorena;Villarreal, Elmer Rolando
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The use of photovoltaic solar panels in electricity generation is becoming increasingly common, both in large-scale systems and in autonomous low-energy consumption systems. In this sense, in order to maximize the use of the energy generated, the panel must always operate at the maximum power point (MPP). The objective of this study is to conduct a comparative study between two techniques for tracking the maximum power point (MPPT): the traditional Perturbation and Observation (P&O) method and the Fuzzy Logic method. The photovoltaic system was modeled in MATLAB/Simulink® to represent the V-I…mehr

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Produktbeschreibung
The use of photovoltaic solar panels in electricity generation is becoming increasingly common, both in large-scale systems and in autonomous low-energy consumption systems. In this sense, in order to maximize the use of the energy generated, the panel must always operate at the maximum power point (MPP). The objective of this study is to conduct a comparative study between two techniques for tracking the maximum power point (MPPT): the traditional Perturbation and Observation (P&O) method and the Fuzzy Logic method. The photovoltaic system was modeled in MATLAB/Simulink® to represent the V-I characteristic curve of the PV module, which is based on data available in commercial photovoltaic panel catalogs. Based on the simulation results, a comparative study was conducted between the control techniques, which led to the conclusion that the controller using Fuzzy presented better performance and efficiency in maintaining the MPP than the control based on the P&O technique.
Autorenporträt
Graduated in Energy Engineering (2012) and Master in Communication and Automation Systems (2014) from the Federal Rural University of the Semi-Arid Region (UFERSA). Currently (2016) she is a doctoral student in the Graduate Program in Electrical and Computer Engineering (PPGEEC) at the Federal University of Rio Grande do Norte (UFRN).