基于遗传算法的过流继电器优化协调

M. Asadi, H. Askarian Abyaneh, M. Mahmoodan, R. Naghizadeh, A. Koochaki
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引用次数: 19

摘要

为了优化过流(OC)继电器的协调,采用了单纯形、两相单纯形和双单纯形等线性规划技术。另一种优化协调方案的方法是利用遗传算法等人工智能系统。本文提出了一种基于遗传算法的OC继电器优化协调的新方法。在优化过程中,我们同时考虑了直流继电器的时间整定乘数(TSM)和插头整定乘数(PSM)。大多数OC继电器只接受离散值作为TSM和PSM,您应该将最终答案更改为离散形式,这可能会破坏优化。本文将答案的量化作为优化过程的一部分,因此输出是离散的TSM和PSM优化。本文的新颖之处在于在TSM的基础上同时考虑了PSM来处理连续和离散TSM和PSM的不协调问题。所得结果令人鼓舞,可作为协调OC继电器的有效工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal Overcurrent relays coordination using genetic algorithm
For optimal co-ordination of overcurrent (OC) relays, linear programming techniques such as simplex, two- phase simplex and dual simplex are used. Another way of optimal coordination program is using artificial intelligent system such as genetic algorithm (GA). In this paper a new approach will be used for optimal coordination of OC relays based on genetic algorithm. In this work we take into account both time setting multiplier (TSM) and plug setting multiplier (PSM) of OC relays in optimization procedure. Most OC relays accept only discrete values as TSM and PSM, and you should change your final answers to discrete form and this may corrupt the optimization. In this paper the act of quantizing the answers is taken into account as a part of optimization procedure, so the outputs are optimized discrete TSM's and PSM's. The novelty of the paper is taking into account the PSM in addition to TSM to handle miscoordination problems both for continues and discrete TSM and PSM. The results obtained are quite encouraging and will be useful as an effective tool for coordination OC relays.
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