DocumentCode :
167311
Title :
Hybrid Metaheuristic for Annual Hydropower Generation Optimization
Author :
Nakib, Amir ; Talbi, El-Ghazali ; Fuser, Alain
Author_Institution :
Lab. LISSI, Univ. Paris, Creteil, France
fYear :
2014
fDate :
19-23 May 2014
Firstpage :
412
Lastpage :
419
Abstract :
In this paper, an hybrid metaheuristic based solution is proposed to solve the annual optimal hydro generation scheduling problem. The problem of the hydro generation scheduling is formulated as a continuous non-linear optimization problem and solved using enhanced combination of metaheuristics: random greedy, evolutionnary algorithm and, pseudo dynamic programming. The obtained results upon one year of the application of the proposed method on the horizon of one year of hydropower generation (while in the literature most authors are limited to one week) demonstrate the efficiency of the proposed algorithm.
Keywords :
dynamic programming; evolutionary computation; greedy algorithms; hydroelectric generators; hydroelectric power; hydroelectric power stations; nonlinear programming; random processes; annual hydropower generation optimization; annual optimal hydro generation scheduling problem; continuous nonlinear optimization problem; evolutionnary algorithm; hybrid metaheuristic based solution; pseudodynamic programming; random greedy algorithm; Heuristic algorithms; Optimization; Production; Reservoirs; Security; Turbines; continuous optimization; evolutionary algorithm; hydropower; metaheuristics; scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International
Conference_Location :
Phoenix, AZ
Print_ISBN :
978-1-4799-4117-9
Type :
conf
DOI :
10.1109/IPDPSW.2014.53
Filename :
6969417
Link To Document :
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