NDLI: Differential Evolution Ant Colony Optimization (DEACO) technique in solving Economic Load Dispatch problem

Content Provider	IEEE Xplore Digital Library
Author	Rahmat, N.A. Musirin, I.
Copyright Year	2012
Description	Author affiliation: Faculty of Electrical Engineering, Universiti Teknologi MARA, Malaysia (Rahmat, N.A.; Musirin, I.)
Abstract	Electric utilities are the companies responsible for ensuring energy supply meets their customers' requirement. While ensuring the energy is generated in the right amount, they have to guarantee that the energy is generated within feasible cost. Economic Load Dispatch (ELD) problem involves the scheduling of generating unit outputs that can satisfy load demand at minimum operating cost. Several approaches have been applied to yield the best solution for the problem, such as Genetic Algorithm, Bees Algorithm and Neural Network Algorithm. This paper presents Differential Evolution Ant Colony Optimization (DEACO) to optimize Economic Load Dispatch in power system. Implementation of the IEEE Reliability Test System (RTS) demonstrated that this technique is feasible to crack the economic problem. Comparative studies with respect to ACO and the traditional ELD techniques designate that the proposed DEACO outperformed these two techniques.
Starting Page	263
Ending Page	268
File Size	357735
Page Count	6
File Format	PDF
ISBN	9781467306607
e-ISBN	9781467306621
DOI	10.1109/PEOCO.2012.6230872
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-06
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Economics Ant colony optimization Differential Evolution Ant Colony Optimization (DEACO) Ant Colony Optimization (ACO) Pheromone Generators Mathematical model Optimization Equations Engines Differential Evolution (DE) Economic Load Dispatch (ELD)
Content Type	Text
Resource Type	Article

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