Modelo multiobjetivo de alocação e dimensionamento de geração distribuída para redes de distribuição

• Ano de defesa: 2018
• Autor(a) principal: Zanin Júnior, Paulo Sérgio
• Orientador(a): Garcés Negrete, Lina Paola
• Banca de defesa: Garcés Negrete, Lina Paola, Brigatto, Gelson Antônio Andrêa, Franco, Edgar Manuel Carreno, Brito, Leonardo da Cunha
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Goiás
• Programa de Pós-Graduação: Programa de Pós-graduação em Engenharia Elétrica e da Computação (EMC)
• Departamento: Escola de Engenharia Elétrica, Mecânica e de Computação - EMC (RG)
• País: Brasil
• Palavras-chave em Português: Algoritmos genéticos; Conjunto de pareto; Métrica maximin; Geração distribuída
• Palavras-chave em Inglês: Distributed generation; Genetic algorithm; Maximin metric; Pareto set
• Área do conhecimento CNPq: ENGENHARIA ELETRICA::ELETRONICA INDUSTRIAL, SISTEMAS E CONTROLES ELETRONICOS
• Link de acesso: http://repositorio.bc.ufg.br/tede/handle/tede/8442

Distributed generation represents a new paradigm to the electricity offer expansion in distribution networks, which has been studied in several aspects. This dissertation aims to propose a multi-objective sizing and siting analysis model to assist the distributed generation units planning, based on three perspectives of concern: technical aspect, from the distribution company viewpoint, financial aspect, from the distributed generation owner’s viewpoint, and social-environmental aspect, from the society viewpoint. In this analysis, a genetic algorithm and the Maximin metric are implemented to obtain a Pareto optimal solutions set. As to decision-making analysis, the present value distributed generators net income; minimum losses set; and the Max-Min approximation are used to choose a final solution from the Pareto set. Study cases are accomplished using distribution networks by the proposed model and Pareto-sets are obtained, which allow the view of the best solutions. The mentioned decision-making analysis is applied to capture one of the Pareto-set solutions. Therefore, the results enable the choice of a distributed generation siting and sizing set and also allow complementary analysis referring to generation sources and the model itself.