DocumentCode :
3573091
Title :
Short-term hydrothermal scheduling based on adaptive chaotic real coded genetic algorithm
Author :
Na Fang ; Jianzhong Zhou ; Jimin Ma
Author_Institution :
Sch. of Hydropower & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2014
Firstpage :
3412
Lastpage :
3416
Abstract :
This paper proposes an adaptive chaotic real coded genetic algorithm (ACRCGA) to solve short-term hydrothermal scheduling (SHS) problem. Adaptive crossover and mutation operator is introduced to improve the global search ability. Meantime, chaotic local search is incorporated into RCGA to enhance the local search ability. An effective constraints handling method for SHS problem is designed to deal with complicated constraints. Finally, the proposed method is applied to a hydrothermal system. The simulation results show that the proposed ACRCGA is superior to other optimization method in quality and efficiency.
Keywords :
genetic algorithms; scheduling; search problems; ACRCGA; SHS problem; adaptive chaotic real coded genetic algorithm; adaptive crossover; global search; short-term hydrothermal scheduling; Genetic algorithms; Optimal scheduling; Reservoirs; Scheduling; Sociology; Statistics; adaptive crossover and mutation; chaotic local search; constraints handling; real coded genetic algorithm; short-term hydrothermal scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7053282
Filename :
7053282
Link To Document :
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