Sistema computacional para dimensionamento de sistemas de geração de energia eólica utilizando redes neurais artificiais

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Ferques, Rafael Gil lattes
Orientador(a): Nogueira, Carlos Eduardo Camargo lattes
Banca de defesa: Nogueira, Carlos Eduardo Camargo lattes, Siqueira, Jair Antonio Cruz lattes, Moreira, Carlos Roberto lattes
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual do Oeste do Paraná
Cascavel
Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Energia na Agricultura
Departamento: Centro de Ciências Exatas e Tecnológicas
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://tede.unioeste.br/handle/tede/2970
Resumo: The objective of this work was the development of a computational application for the design of wind power generation systems in small-scale On-Grid and Off-Grid installations, using a user friendly and interactive process. For this, the concepts of artificial intelligence were used in conjunction with genetic algorithms, to verify the technical and economic viability of the implantation of the wind power generation system. Also, implement an integrated database, containing technical specifications and component costs of a wind system. The encoding of the application was done through the languages Java, C, C++ and the database in MySQL language. For the development of the neural networks and genetic algorithms, it was used to the Encog library. With wind data, demand, energy consumption and type of configuration desired, the application performs the sizing of the wind system and then, using artificial intelligence, verifies the best scenario for the project. Following is a report with the physical and financial information. The calculations used for the design were according to Pinho et al. (2008), CRESESB (2014) and Albano (2009). The application has proven effective in scaling and economical analysis of small wind systems, allowing fast and simple simulation of On-Grid systems and Off-Grid systems.