DocumentCode
3325224
Title
Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization
Author
Hamid, Z. ; Musirin, I. ; Rahim, M.N.A. ; Kamari, N.A.M.
Author_Institution
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear
2012
fDate
12-13 Jan. 2012
Firstpage
59
Lastpage
64
Abstract
A new method to select suitable generators for the purpose of power scheduling has been proposed in this paper, namely Fast Voltage Stability Index Generation Tracing (FVSI-GT). Contrary to previous power tracing techniques which select the generators based on the magnitude of traced power, the proposed technique performs the generator selection based on the stability index contributed by individual system´s generator. After tracing the contributed stability index, the sizing process of generators´ power to be dispatched has been performed via a new hybrid optimization algorithm; Blended Crossover Continuous Ant Colony Optimization (BX-CACO). From experiment and validation on IEEE 30 bus reliability test system (RTS), it is revealed that FVSI-GT exhibits great performance as the method capable to select exact generators with the enhancement of system´s static stability, losses and fuel cost minimization with fast optimization via BX-CACO.
Keywords
IEEE standards; ant colony optimisation; load dispatching; power generation scheduling; power system stability; BX-CACO; IEEE 30 bus reliability test system; blended crossover continuous ant colony optimization; effective power scheduling; fast voltage stability index generation tracing; generators; power tracing techniques; Generators; Indexes; Minimization; Optimization; Power system stability; Stability criteria; BX-CACO; FVSI-GT; power scheduling; stability index based ranking;
fLanguage
English
Publisher
ieee
Conference_Titel
ICT and Knowledge Engineering (ICT & Knowledge Engineering), 2011 9th International Conference on
Conference_Location
Bangkok
Print_ISBN
978-1-4577-2161-8
Type
conf
DOI
10.1109/ICTKE.2012.6152415
Filename
6152415
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