Gerenciamento ótimo de energia em microrredes

• Ano de defesa: 2018
• Autor(a) principal: Santos, André Quites Ordovás
• Orientador(a): Almeida, Adriano Batista de
• Banca de defesa: Franco, Edgar Manuel Carreño , Leme, Rafael Coradi
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Paraná; Foz do Iguaçu
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Elétrica e Computação
• Departamento: Centro de Engenharias e Ciências Exatas
• País: Brasil
• Palavras-chave em Português: Redes inteligentes de energia elétrica; Microrredes inteligentes de energia elétrica; Gerenciamento ótimo de energia; Geração distribuída; Energias renováveis
• Palavras-chave em Inglês: Smart grids; Intelligent microgrids; Energy management; Distributed generation; Renewable energy sources
• Área do conhecimento CNPq: ENGENHARIA ELETRICA::SISTEMAS ELETRICOS DE POTENCIA
• Link de acesso: http://tede.unioeste.br/handle/tede/4118

The expected advance of the smart grids, with all its anticipated benefits like improved reliability and reduced environmental impacts, depends greatly on the technical-economical and regulatory viability of the so-called intelligent microgrids. Intelligent microgrids are considered as essential components of the future smart grids which, in their advanced stage, are expected to be structured as large networks of interconnected intelligent microgrids. Among the existing challenges to a wider adoption of the intelligent electrical energy microgrids technology, the efficiency and simplification of the energy management systems, responsible for the optimal operation of the energy resources available in the system, are often viewed as a primary necessity, especially in the so-called connected or normal mode, in which microgrids are expected to operate most of the time. The initial investment in deploying an intelligent microgrid is still considered very high. This paper presents a linear mixed-integer optimization model to solve the energy management problem in a microgrid in connected mode, having as objective the cost minimization, considering a 24-hour horizon, called day-ahead model. Two real-time optimization models are presented, operating in a 5-minute time horizon, with centralized and decentralized strategies, aiming at keeping the power balance optimally, considering the natural deviations of realized demand and supply, regarding the day-ahead forecast. The model presented here takes in consideration some of the most common components of the modern microgrids, such as renewable intermittent sources, non-renewable dispatchable sources, and energy storage systems. The microgrid is supposed as being able to sell and buy energy from the distribution system, in a scenario with varying energy market prices, also considering the contracted demand. The model is then applied, through computer simulations, to a typical microgrid architecture. The results are then presented and analyzed.