Desenvolvimento e avaliação de algoritmo para otimização do desempenho de sistemas fotovoltaicos sob sombreamento parcial

Abstract

This thesis addresses the development and evaluation of an advanced algorithm designed to optimize the performance of photovoltaic systems under partial shading conditions, a common challenge in photovoltaic installations that significantly compromises energy generation effici-ency. Partial shading produces multiple power peaks in the characteristic curve of photovoltaic modules, complicating the identification of the global maximum power point using traditional maximum power point tracking techniques, such as the perturb and observe method. To overcome this limitation, a global maximum power point tracking (GMPPT) algorithm was implemented, which performs a more comprehensive search for power peaks, identifying the global maximum power point even under adverse shading conditions. The implementation of the algorithm involved the modeling of the photovoltaic panels and the boost-type DC-DC converter, including its control, as well as the integration of the algorithm into the PSIM simulation platform. The results demonstrated that the GMPPT algorithm significantly enhances energy extraction, improving the overall efficiency of the photovoltaic system. This highlights its potential practical application in solar energy generation systems, particularly in urban environments where partial shading is common.