Title :
Generation scheduling using genetic algorithm based hybrid techniques
Author :
Dahal, Keshav P. ; Galloway, Stuart J. ; Burt, Graeme M. ; McDonald, Jim R.
Author_Institution :
Centre for Electr. Power Eng., Strathclyde Univ., Glasgow, UK
Abstract :
The solution of generation scheduling (GS) problems involves the determination of the unit commitment (UC) and economic dispatch (ED) for each generator in a power system at each time interval in the scheduling period. The solution procedure requires the simultaneous consideration of these two decisions. Researchers have focused much attention on new solution techniques to GS. This paper proposes the application of a variety of genetic algorithm (GA) based approaches and investigates how these techniques may be improved in order to more quickly obtain the optimum or near optimum solution for the GS problem. The results obtained show that the GA-based hybrid approach offers an effective alternative for solving realistic GS problems within a realistic timeframe
Keywords :
genetic algorithms; power generation dispatch; power generation economics; power generation scheduling; economic dispatch; generation scheduling; genetic algorithm based hybrid techniques; power system; unit commitment; Environmental economics; Expert systems; Genetic algorithms; Helium; Hybrid power systems; Power generation; Power generation economics; Power system economics; Scheduling; Testing;
Conference_Titel :
Power Engineering, 2001. LESCOPE '01. 2001 Large Engineering Systems Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-7107-0
DOI :
10.1109/LESCPE.2001.941630