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
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;
Conference_Titel :
Power Tech Proceedings, 2001 IEEE Porto
Conference_Location :
Porto
Print_ISBN :
0-7803-7139-9
DOI :
10.1109/PTC.2001.964734