DocumentCode
1871430
Title
Economic dispatch solution using a genetic algorithm based on arithmetic crossover
Author
Yalcinoz, T. ; Altun, H. ; Uzam, M.
Author_Institution
Dept. of Electr. & Electron. Eng., Nigde Univ., Turkey
Volume
2
fYear
2001
fDate
2001
Abstract
In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (IHN), a fuzzy logic controlled genetic algorithm (FLCGA), an advance engineered-conditioning genetic approach (AECGA) and an advance Hopfield NN approach (AHNN)
Keywords
Hopfield neural nets; control system synthesis; fuzzy control; genetic algorithms; load dispatching; neurocontrollers; optimal control; power system control; power system economics; advance engineered-conditioning genetic approach; arithmetic crossover; economic dispatch solution; elitism; fuzzy logic control; genetic algorithm; improved Hopfield NN approach; mutation; operating policies; solution quality; Arithmetic; Costs; Environmental economics; Fuel economy; Fuzzy logic; Genetic algorithms; Power generation economics; Power system economics; Power system modeling; Power system reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Tech Proceedings, 2001 IEEE Porto
Conference_Location
Porto
Print_ISBN
0-7803-7139-9
Type
conf
DOI
10.1109/PTC.2001.964734
Filename
964734
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