Diagnóstico hidroenergético e otimização operacional pela aplicação de algoritmos genéticos, de uma estação elevatória de água

• Ano de defesa: 2018
• Autor(a) principal: Henriques, Kenny Rogers da Silva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Engenharia Mecânica; Programa de Pós-Graduação em Engenharia Mecânica; UFPB
• Palavras-chave em Português: Sistemas de abastecimento de água; Diagnóstico hidroenergético; Otimização operacional; Algoritmos genéticos; Water supply systems; Hydropower diagnostics; Operational optimization; Genetic algorithms; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/12952

Multi-reservoir water supply systems, multiple pump-pump assemblies associated with demand variations over a one-day supply make their operation and management routines much more complex. In this way it is possible to use mathematical and hydraulic simulation and modeling software to optimize the operation of these types of systems. The objective of this work was to perform a hydroenergetic diagnosis in a real supply system and application of Genetic Algorithms to optimize its operational routines to drive the pump sets and management of water levels in the reservoirs aiming at reducing pumping costs. The methodology presented in this paper proposes the hydroenergetic analysis of the current system and two other scenarios, the first with the operational routines optimized by the application of GAs and the second recital in addition to optimized operating routines, structural interventions such as the replacement of the propulsion sets , reduction in water losses and reduction of pumped volume. The hydropower diagnosis showed substantial losses of water and energy in the current system. The results obtained after interventions of the operational routines by the genetic algorithm, also integrated the reduction of losses of water in the supply network, presented quite satisfactory. The realization of a hydroenergetic diagnosis associated with the application of genetic algorithms as a tool to optimize the operational routines of water systems with multiple reservoirs and multiple pumps were efficient and applicable to the actual system presented, resulting in substantial reductions in pumping operating costs.