PPG.EGPSA/ITEGAM

URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/1

A comunidade dispõe da produção técnica e científica do Programa de Pós-graduação em Engenharia, Gestão de Processos, Sistema e Ambiental (PPG.EGPSA) do Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM), fruto da atividade de pesquisa e desenvolvimento (P&D). É possível acessar os trabalhos de conclusão do programa de pós-graduação, artigos e livros vinculados a pesquisa, desenvolvimento, inovação e extensão.

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Assunto: search.filters.subject.Sistemas Fotovoltaicos

Resultados da Pesquisa

Agora exibindo 1 - 2 de 2
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    Smart energy: application of the photovoltaic system using genetic algorithms for decision making in industry 4.0
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone da; ALMEIDA, Anderson Alexandre Silva de; MONTEIRO, Odilon Bentes; RIBEIRO, Paulo Francisco da Silva; NASCIMENTO FILHO, Alarico Gonçalves do; LEITE, Jandecy Cabral
    The growing demand for sustainable solutions and the digitalization of industrial processes have driven the adoption of photovoltaic systems and advanced decision-making technologies. In the context of Industry 4.0, where automation and artificial intelligence are fundamental, these systems stand out as a clean energy alternative, promoting savings and reducing pollutant emissions. This study aims to develop a photovoltaic energy control model that uses genetic algorithms to optimize energy efficiency in industrial environments, reducing costs and dependence on non-renewable sources. The methodology included the computational modeling of a photovoltaic system and the application of genetic algorithms to optimize parameters such as panel angle and operating hours, adapting the system in real time to variable consumption and generation conditions. The results showed that the use of genetic algorithms increased the system's efficiency by up to 20% compared to traditional methods, as well as minimizing consumption from the electricity grid at peak times. This study reinforces the importance of artificial intelligence in optimizing renewable resources, contributing to energy efficiency and sustainability in Industry 4.0.
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    Smart Energy: aplicação do sistema fotovoltaico utilizando algoritmos genéticos para tomada de decisão na indústria 4.0
    (Instituto Nacional da Propriedade Industrial (INPI), 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone da
    This document certifies the registration of the "Smart Energy" software, which employs genetic algorithms for decision-making in the context of Industry 4.0. The application focuses on photovoltaic systems, aiming to optimize industrial processes through advanced computational techniques.