Otimização multiobjetivo evolutiva da operação de sistemas de reservatórios multiusos

• Ano de defesa: 2014
• Autor(a) principal: Luís Antônio Scola
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Algoritmos evolutivos; Geração de energia; Algoritmos genéticos; Planejamento hidroelétrico; Otimização multiobjetivo; Engenharia elétrica
• Link de acesso: http://hdl.handle.net/1843/BUOS-9QEH7F

An evolutionary multiobjective optimization approach, based on NSGA-II classic algorithm, for the study of multiple water usages in multiple interlinked reservoirs, including both power generation objectives and of navigability on the river, was proposed in this thesis. The algorithm was adapted in order to cope with specific problem feature. The main modification, which caused the major enhancement in the algorithm performance, is a new encoding scheme that allows the implicit handling of most of the constraints involved in the problem. Starting from classic formulation, three alternatives for constraints treatment were proposed culminating in an unconstrained and limited optimization model by using a new decision variable: monthly available volume fraction. The algorithm proposed was firstly applied to one reservoir system, considering two objectives linked to energy generation. Finally, the algorithm proposed was applied to a subsystem of the Brazilian electric system, composed of five reservoirs with five hydroelectric power stations. For this last case, a multiobjective analysis for four different scenarios was applied allowing the assessment of the algorithm's performance, related to energy generation objectives and, in another scenario, the inclusion of a third one, which involves the navigability on the river between two reservoirs. The obtained results showed that the proposed methodology overcomes the problems of diversity loss and premature convergence, problems encountered in the implementation of the original decision variables. The information generated by the optimization algorithm, demonstrated the usefulness in the making-decision process in planning the operation of reservoirs systems. The results showed that it is possible to quantify the cost of any new use of water, in terms of opportunity cost, which can be measured by financial return from the sallings of energy produced.