Otimização multiobjetivo para operação de estações elevatórias : estudo de caso Campo Verde/MT
Ano de defesa: | 2018 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Mato Grosso
Brasil Faculdade de Arquitetura, Engenharia e Tecnologia (FAET) UFMT CUC - Cuiabá Programa de Pós-Graduação em Recursos Hídricos |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://ri.ufmt.br/handle/1/3455 |
Resumo: | One of the large difficulties of SAA faced by sanitation companies is to serve their users with adequate and compatible flows and pressures, in view of the rapid population growth of cities, as well as changes in demand throughout the day. For this, it is necessary to use pumping stations, which are the main responsible for the expenses with electric energy in the sanitation companies (about 90%), besides conferring reliability to the SAA. Thus, the objective of this work was to perform multiobjective optimization for operation (operational cost, hydraulic and mechanical reliability) of water pumping stations for public supply, having as study area the municipality of Campo Verde/MT. The data for the study were made available by the municipality's sanitation company (Nascente do Xingu / Águas de Campo Verde). The methodology employed basically involved three steps: data processing; determination of water consumption profiles and; development of the multiobjective optimization model (MOM). DEPS - Differential Evolution & Particle Swarm Optimization - was the optimization algorithm used by the classical non-dominated solution generation technique known as the weights method. From the ten scenarios defined, the scenario chosen as the preference of the decision maker as a form of operation, did not present significant efficiency in the objective functions considered, since the optimization model was very restrictive and with little flexibility. The operating rules for the reference situation and optimized system presented a large amount of pump activation. On the other hand, the weights method proved capable of generating non-dominated solutions to the problem in question. |