Comparison between algorithms for MPP search in photovoltaic systems in different irradiance and temperature conditions

Kaio  Martins Ramos; Felipe J. S. Vasconcelos; Josias  G. Batista; Darielson  A. Souza; Gabriel  Freitas Machado; Paulo  Daving Lima de Oliveira; Arthur Plínio  de Souza Braga

doi:10.48011/asba.v2i1.1627

Kaio Martins Ramos Universidade Federal do Ceará
Felipe J. S. Vasconcelos Universidade Federal do Ceará
Josias G. Batista Instituto Federal de Educação Ciência e Tecnologia do Ceará
Darielson A. Souza Universidade Federal do Ceará
Gabriel Freitas Machado Universidade Federal do Ceará
Paulo Daving Lima de Oliveira Universidade Federal do Ceará
Arthur Plínio de Souza Braga Universidade Federal do Ceará

DOI: https://doi.org/10.48011/asba.v2i1.1627

Keywords: Energy, Photovoltaic, MPPT, Dynamic conditions, Intelligent algorithms

Abstract

The generation of electric energy is an essential factor for society, both for economic and social development. Within this context, renewable sources have been gaining ground, such as photovoltaic systems. However, its efficiency presents non-linear characteristics due to thresholds in temperature and irradiance, mainly caused by climatic factors. This problem affects the load power supply, thus loosing effectiveness. To minimize this problem, it is necessary
the operation at the maximum power point (MPP), made by means of some systems, called Maximum Power Point Trackers (MPPT). This paper discusses the implementation of two intelligent MPPT algorithms: the fisrt one using a metaheuristic called Radial Movement Optimization (RMO), and the second one based on the cooperation of RMO, and a traditional MPPT, called Perturb and Observe (P&O).The results show that although providing stable outputs after finding the MPP, the metaheuristic presents a larger oscillation during the search procedure in comparison with P&O.