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Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization

By: Kamari, N.A.M.; Rahim, M.N.A.; Musirin, I.; Hamid, Z.;

2012 / IEEE / 978-1-4577-2162-5

Description

This item was taken from the IEEE Conference ' Effective power scheduling via Blended Crossover Continuous Ant Colony Optimization ' 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.