Application of Multi-Objective Evolutionary Optimization Algorithms to Reactive Power Planning Problem
Use this link to cite this item : https://ir.lib.hiroshima-u.ac.jp/00025642
ID | 25642 |
file | |
creator |
Eghbal, Mehdi
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NDC |
Technology. Engineering
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abstract | This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization problem. Minimizing the total incurred cost and maximizing the amount of Available Transfer Capability (ATC) are defined as the main objective functions. The proposed approaches have been successfully tested on IEEE 14 bus system. As a result a wide set of optimal solutions known as Pareto set is obtained and encouraging results show the superiority of the proposed approaches and confirm their potential to solve such a large scale multi-objective optimization problem.
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journal title |
Fourth International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2008
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start page | 165
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end page | 170
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date of issued | 2008-12
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publisher | IEEE SMC Hiroshima Chapter
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issn | 1883-3977
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language |
eng
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nii type |
Conference Paper
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HU type |
Conference Papers
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DCMI type | text
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format | application/pdf
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text version | publisher
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rights | (c) Copyright by IEEE SMC Hiroshima Chapter.
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department |
Graduate School of Engineering
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