过流继电器协调的改进灰狼优化算法

N. Jamal, M. Sulaiman, O. Aliman, Z. Mustaffa, M. Mustafa
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引用次数: 1

摘要

近年来,自然启发算法(NIA)已被应用于生物医学工程、电子工程、计算机科学等优化问题的各个领域。NIA在解决这些领域的优化问题方面取得的成就成为将NIA中的一种即灰狼优化器(GWO)应用于过流继电器协调问题的动力。然而,GWO的现状存在着勘探不足的问题。因此,本文提出了对GWO的改进,以加强对原始GWO的探索。为了使主继电器在近端故障时的运行时间最小,对GWO (IGWO)进行了改进,找到了时间乘法器(TMS)和插头设置(PS)的最优值。通过全面的仿真研究,证明了与原始GWO相比,所提出的改进技术的可靠性和效率。生成的结果证实了所提出的IGWO能够改善过流继电器协调问题的目标函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Grey Wolf Optimization Algorithm for Overcurrent Relays Coordination
Recently, nature inspired algorithms (NIA) have been implemented to various fields of optimization problem such as biomedical engineering, electrical engineering, computer science and etc. The achievement of NIA in solving optimization in these fields becoming the motivation to apply one of the NIA namely Grey Wolf Optimizer (GWO) into overcurrent relay coordination problem. However, the current state of GWO suffers lack of exploration problem. Hence, the improvement of GWO has been proposed in this paper to enhance the exploration of original GWO. The improvement of GWO (IGWO) is implemented in finding the the optimal value of the Time Multiplier Setting (TMS) and Plug Setting (PS) in order to minimize the primary relays' operating time at the near end fault. Comprehensive simulation studies have been performed to demonstrate the reliability and efficiency of the proposed modification technique compared to the original GWO. The generated results have confirmed the proposed IGWO is able to improve the objective function of the overcurrent relay coordination problem.
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