Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings
Pages263-268
Number of pages6
DOIs
Publication statusPublished - 20 Aug 2012
Event2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Melaka, Malaysia
Duration: 06 Jun 201207 Jun 2012

Publication series

Name2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings

Other

Other2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012
CountryMalaysia
CityMelaka
Period06/06/1207/06/12

Fingerprint

Ant colony optimization
Economics
Electric utilities
Operating costs
Genetic algorithms
Scheduling
Cracks
Neural networks
Costs
Industry

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Fuel Technology

Cite this

Rahmat, N. A., & Musirin, I. (2012). Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem. In 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings (pp. 263-268). [6230872] (2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings). https://doi.org/10.1109/PEOCO.2012.6230872
Rahmat, Nur Azzammudin ; Musirin, I. / Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem. 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings. 2012. pp. 263-268 (2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings).
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Rahmat, NA & Musirin, I 2012, Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem. in 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings., 6230872, 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings, pp. 263-268, 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012, Melaka, Malaysia, 06/06/12. https://doi.org/10.1109/PEOCO.2012.6230872

Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem. / Rahmat, Nur Azzammudin; Musirin, I.

2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings. 2012. p. 263-268 6230872 (2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Rahmat NA, Musirin I. Differential Evolution Ant Colony Optimization (DEACO) technique in solving economic load dispatch problem. In 2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings. 2012. p. 263-268. 6230872. (2012 IEEE International Power Engineering and Optimization Conference, PEOCO 2012 - Conference Proceedings). https://doi.org/10.1109/PEOCO.2012.6230872