Title :
Genetic algorithms applied to hydrothermal system scheduling
Author :
Carneiro, A.A.F.M. ; Leite, P.T. ; Filho, D. Silva ; Carvalho, A.C.P.L.F.
Author_Institution :
Dept. of Electr. Eng., Sao Paulo Univ., Brazil
Abstract :
This paper presents a new method to solve the optimal scheduling of hydrothermal power systems (HPSs). This is performed using an artificial intelligence technique, genetic algorithms (GAs). A few tests have been carried out on a subsystem of the Southeast Brazilian System. The complexity level of the simulations is gradually increased and the main aspects of the optimal system operation are highlighted. The results achieved with the new technique are compared with results from traditional nonlinear optimization techniques and the advantages of GAs are showed both in the optimization process and in the lower operative cost obtained
Keywords :
genetic algorithms; hydrothermal power systems; power generation planning; power generation scheduling; Brazil; artificial intelligence; genetic algorithms; hydrothermal power systems; operating costs; optimal scheduling; optimization process; power generation; Cost function; Genetic algorithms; Optimal scheduling; Power engineering and energy; Power generation; Power system planning; Power system simulation; Processor scheduling; Reservoirs; Water resources;
Conference_Titel :
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4754-4
DOI :
10.1109/ICPST.1998.729024