Thumbnail Image
Publication

Generation scheduling using genetic algorithm based hybrid techniques

Dahal, Keshav P.
; 
Galloway, S.J.
; 
Burt, G.M.
; 
McDonald, J.R.
Publication Date
2001
End of Embargo
Supervisor
Keywords
Unit commitment/Economic dispatch, Genetic algorithms, Hybrid approach, Generation scheduling
Rights
Copyright © [2001] IEEE. Reprinted from Proceedings of Large Engineering Systems Conference on Power Engineering (LESCOPE2001). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubspermissions@ ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
cb
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
Institution
Department
Awarded
Embargo end date
Collections
Engineering and Digital Technology Publications
Show all metadata
Files
Thumbnail Image
dahal11.pdf
Adobe PDF, 215.78 KB
Additional title
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. In recent years 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.
URI
http://hdl.handle.net/10454/2598
Version
Published version
Citation
Dahal K. P., Galloway, S. J., Burt, G. M. and McDonald, J. R. (2001) Generation scheduling using genetic algorithm based hybrid techniques. In: Proceedings of Large Engineering Systems Conference on Power Engineering (LESCOPE2001), 11-13th July, Nova Scotia, Canada. New York: IEEE. pp. 74- 78.
Link to publisher’s version
Link to published version
Link to Version of Record
https://doi.org/10.1109/LESCPE.2001.941630
Type
Conference paper
Qualification name
Notes