Metodologia de blocos funcionais com previsão de grandezas elétricas para sistemas de distribuição inteligentes

• Ano de defesa: 2018
• Autor(a) principal: Garcia, Enoque Dutra
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Engenharia Elétrica; UFSM; Programa de Pós-Graduação em Engenharia Elétrica; Centro de Tecnologia
• Palavras-chave em Português: Recursos de energia distribuídos; Recursos flexíveis distribuídos; Previsão; Controle do sistema de energia; Redes elétricas inteligentes; Distributed energy resources; Distributed flexible resources; Forecasting; Power system control; Smart grids; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: http://repositorio.ufsm.br/handle/1/15288

Distribution systems are undergoing structural and topological changes, mainly due to the influence of the new distributed energy resources inserted along the feeders. In this context, the growth of the Smart Grids requires the evolution of the control and operation tools, since the decisions-making should promote proactive actions. In this sense, the present thesis proposes a method for subdividing the distribution system into grid functional blocks, associated to a method of forecasting distributed electric quantities. The functional blocks allow the assets to be organized in a way to provide sufficient information to perform advanced analyzes of a geoelectric region. The proactive decisions in the grid functional blocks are then taken from the very short term forecast of variables (voltage, current, active power and reactive power). These forecasts are based on an innovative method of selection of forecasting techniques, which takes into account the online and historical information for the performance ranking of forecasting techniques. The developed methodologies provide greater flexibility for the Smart Grids regarding to the dynamic changes that occur in the distribution grids in the presence of distributed flexible resources, demand management, Volt-VAR Optimization, Conservation Voltage Reduction, protection, automatic reconfiguration, self-healing, storage and electric vehicles.