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用于无功功率优化的新型增强人工蜂群算法(JA - ABC5)

New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization.

作者信息

Sulaiman Noorazliza, Mohamad-Saleh Junita, Abro Abdul Ghani

机构信息

School of Electrical & Electronic Engineering, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia.

College of Engineering, King Saud University, Muzahmyiah Campus, Riyadh 11451, Saudi Arabia.

出版信息

ScientificWorldJournal. 2015;2015:396189. doi: 10.1155/2015/396189. Epub 2015 Mar 23.

Abstract

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.

摘要

标准人工蜂群(ABC)算法涉及探索和利用过程,为提高性能,这两个过程需要保持平衡。本文提出了一种名为JA - ABC5的改进型ABC算法,通过平衡探索和利用过程来提高收敛速度,并增强达到全局最优的能力。在算法的早期阶段提出了新的步骤以增加利用过程。除此之外,在 employed 和 onlooker - bees 阶段还引入了改进的变异方程,以平衡这两个过程。在27个常用基准函数上分析了JA - ABC5的性能,并对其进行测试以优化无功功率优化问题。性能结果清楚地表明,新提出的算法在收敛速度和实现全局最优方面优于其他对比算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3719/4386549/8f8e6eb89cb9/TSWJ2015-396189.001.jpg

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