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

• Ano de defesa: 2017
• Autor(a) principal: Ferques, Rafael Gil
• Orientador(a): Nogueira, Carlos Eduardo Camargo
• Banca de defesa: Nogueira, Carlos Eduardo Camargo , Siqueira, Jair Antonio Cruz , Moreira, Carlos Roberto
• 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: Energia eólica; Algoritmos genéticos; Aplicativo computacional; Fontes renováveis; Renewable sources
• Palavras-chave em Inglês: Wind Power; Genetic algorithm; Computer application
• Área do conhecimento CNPq: CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://tede.unioeste.br/handle/tede/2970

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.