Title :
Genetic Algorithm for Static Power Economic Dispatch
Author :
Chiang, Chao-Lung
Author_Institution :
Electron. Eng. Dept., Nan Kai Univ. of Technol., Nan Ton, Taiwan
fDate :
March 31 2009-April 2 2009
Abstract :
This research presents an improved genetic algorithm (IGA) to solve static power economic dispatch (SPED) problems of units with valve-point effects and multiple fuels. Few SPED problems related studies have seldom addressed both valve-point loadings and change fuels. The proposed algorithm was compared with the conventional genetic algorithm (CGA), revealing that the proposed IGA is more effective than the CGA, and applies the realistic SPED problem more efficiently than does the CGA.
Keywords :
genetic algorithms; power system economics; change fuels; conventional genetic algorithm; improved genetic algorithm; power system; static power economic dispatch; valve-point loadings; Constraint optimization; Cost function; Dynamic programming; Fuel economy; Genetic algorithms; Genetic engineering; Hopfield neural networks; Power engineering and energy; Power generation economics; Power systems; Genetic algorithm; Power system; economic dispatch;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.440
