Title :
A new genetic algorithm for unit commitment
Author :
Hongwei, Zhao ; Liangting, Yi ; Buyun, Wang ; Gang, Cheng ; Haiping, Yang
Author_Institution :
Dept. of Autom. Eng., Chongqing Logistic Eng. Univ., Chongqing, China
Abstract :
This paper presents a revised genetic algorithm (RGA) for unit commitment (UC). A model to adjust the parameters of the GA automatically with the population evolution and different chromosomes is built. A new stop-rule is also given. In order to examine the proposed method, an example is employed for UC which yields several promising results
Keywords :
genetic algorithms; load distribution; power engineering computing; scheduling; chromosomes; load demand; optimum schedule; parameter adjustment; population evolution; revised genetic algorithm; stop rule; unit commitment; Acceleration; Artificial intelligence; Biological cells; Convergence; Delay; Genetic algorithms; Genetic mutations; Power systems; Robustness; Spinning;
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
DOI :
10.1109/ICIPS.1997.672856
