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Hybridization of Artificial Immune Systems and Sequential Quadratic Programming for Dynamic Economic Dispatch

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Abstract:

Dynamic economic dispatch deals with the scheduling of online generator outputs with predicted load demands over a certain period of time so as to operate an electric power system most economically. This article proposes a hybrid methodology integrating artificial immune systems with sequential quadratic programming for solving the dynamic economic dispatch problem of generating units considering valve-point effects. This hybrid method incorporates artificial immune systems as a base level search, which can give good direction to the optimal region and sequential quadratic programming as a local search procedure, which is used to fine tune that region for achieving the final solution. Numerical results of a ten-unit system have been presented to demonstrate the performance and applicability of the proposed algorithm. The results obtained from the proposed algorithm are compared with those obtained from a hybrid of particle swarm optimization and sequential quadratic programming and a hybrid of evolutionary programming and sequential quadratic programming.

Keywords: artificial immune systems; dynamic economic dispatch; sequential quadratic programming

Document Type: Research Article

DOI: https://doi.org/10.1080/15325000902918941

Affiliations: Department of Power Engineering, Jadavpur University, Kolkata, India

Publication date: 2009-09-01

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