Effect of Population Size for DG Installation using EMEFA
This paper presents a new Embedded Meta Evolutionary-Firefly Algorithm (EMEFA) for DG installation which considers the effect of population size on loss and cost minimization while improving the performance of the system. The proposed EMEFA technique is to alleviate the setback experienced in the Me...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/6567/1/Effect_of_Population_Size_for_DG_Installation_using_EMEFA.pdf http://umpir.ump.edu.my/id/eprint/6567/ http://dx.doi.org/10.1109/PEOCO.2013.6564646 |
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| Summary: | This paper presents a new Embedded Meta Evolutionary-Firefly Algorithm (EMEFA) for DG installation which considers the effect of population size on loss and cost minimization while improving the performance of the system. The proposed EMEFA technique is to alleviate the setback experienced in the Meta-EP and firefly in terms slow convergence and less accurate. Implementation of the proposed technique in minimizing both the distribution losses and fuel cost separately has indicated promising results, while maintaining the voltage at acceptable levels. Assessment on its performance with respect to other optimization techniques revealed that the proposed technique is superior in terms fast convergence and achieving more accurate solution, validated on a chosen IEEE Reliability Test System. |
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