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Tipo: conferenceObject
Título: A Genetic Algorithm Applied to a PWR Turbine Extraction Optimization to Increase Cycle Efficiency
Autor(es): SACCO, Wagner Figueiredo
PEREIRA, Cláudio Márcio do Nascimento Abreu
SCHIRRU, Roberto
Resumo: In nuclear power plants feedwater heaters are used to heat feedwater from its temperature leaving the condenser to final feedwater temperature using steam extracted from various stages of the turbines. The purpose of this process is to increase cycle efficiency. The determination of the optimal fraction of mass flow rate to be extracted from each stage of the turbines is a complex optimization problem. This kind of problem has been efficiently solved by means of evolutionary computation techniques, such as Genetic Algorithms (GAs). GAs, which are systems based upon principles from biological genetics, have been successfully applied to several combinatorial optimization problems in nuclear engineering, as the nuclear fuel reload optimization problem. We introduce the use of GAs in cycle efficiency optimization by finding an optimal combination of turbine extractions. In order to demonstrate the effectiveness of our approach, we have chosen a typical PWR as case study. The secondary side of the PWR was simulated using PEPSE, which is a modeling tool used to perform integrated heat balances for power plants. The results indicate that the GA is a quite promising tool for cycle efficiency optimization.
Palavras-chave: Cycle Efficiency Optimization
Rankine Cycle
Genetic Algorithms
Idioma: eng
País: Brasil
Editor: Instituto de Engenharia Nuclear
Sigla da Instituição: IEN
Tipo de Acesso: openAccess
Data do documento: 2002
Aparece nas coleções:Desenvolvimento de Tecnologia para Sistemas Complexos - Trabalhos de Congresso

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