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
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;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7053282