Title :
A genetic algorithm solution for optimization of the power generation potential in hydroelectric plants
Author :
Pillon Torralba Fernandes, Jessica ; de Barros Correia, Paulo ; Hidalgo, Ieda Geriberto ; Colnago, Glauber Renato
Author_Institution :
Dept. of Energy, Univ. of Campinas - UNICAMP, Campinas, Brazil
Abstract :
This paper presents an optimization model of the power generation potential for either new or repowered hydroelectric plants. It is based on curves that represent the unit efficiency as a function of the nominal output. The objective is to choose the combination of efficiency curve types that maximizes the power generation for certain load levels. The mathematical formulation results in a mixed integer, nonlinear programming problem. Genetic Algorithm is employed to solve this. The operators and parameters of the model are chosen by simulation using the objective function values as a selection method. A case study is carried out for two Brazilian hydroelectric plants: Sobradinho and Ilha Solteira. The results show the importance of the turbines model choice in order to get the maximum benefit of a plant.
Keywords :
genetic algorithms; hydraulic turbines; hydroelectric power stations; integer programming; nonlinear programming; Brazilian hydroelectric plants; Ilha Solteira hydroelectric plant; Sobradinho hydroelectric plant; efficiency curve type; genetic algorithm solution; mixed integer nonlinear programming problem; objective function value; optimization model; power generation potential; turbine model; unit efficiency; Biological cells; Equations; Genetic algorithms; Sociology; Turbines; Velocity control; efficiency curves; genetic algorithm; hydroelectric power plants; turbines;
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
DOI :
10.1109/CEC.2013.6557870
