Title :
Multi-objective optimal reservoir operation
Author :
Scola, Luís A. ; Neto, Oriane M. ; Takahashi, Ricardo H C ; Cerqueira, Sérgio A A G
Author_Institution :
Dept. of Thermal & Fluid Sci., Fed. Univ. of Sao Joao del Rei, São João del Rei, Brazil
Abstract :
The need for the efficient operation of hidropower plants, which provides most of the electrical power consumed in Brazil, is related not only to the issue of energy conservation, but has also been highlighted by the increasing opposition to the construction of new large reservoirs, for ecological and social reasons. In this work, a multi-objective genetic algorithm is applied to problem of the optimization of a single Brazilian hydropower plant, with the objectives of increasing the net energy generation along the year and reducing the peak of demand of non-renewable energy sources. To increase the performance of the algorithm, two new formulations for the problem are proposed, with different ways of dealing with the operational constraints. In comparison with the more traditional approach, this results not only in efficiency gains, but also in an expanded Pareto front, which adds more flexibility to the system, by revealing new possible configurations of system operation.
Keywords :
Pareto optimisation; genetic algorithms; hydroelectric power stations; reservoirs; Brazilian hydropower plant; Pareto front; electrical power; energy conservation; multiobjective genetic algorithm; multiobjective optimal reservoir operation; net energy generation; nonrenewable energy sources; Electronic mail; Hydroelectric power generation; Optimization; Reservoirs; Turbines;
Conference_Titel :
Evolutionary Computation (CEC), 2010 IEEE Congress on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-6909-3
DOI :
10.1109/CEC.2010.5586361