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Immune system memetic algorithm for power distribution network design with load evolution uncertainty

机译:负荷演化不确定的配电网免疫系统模因算法

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摘要

A recent paper, [1], has proposed a methodology for taking into account uncertainties in the load evolution within the design of electric distribution networks. That paper has presented an immunological algorithm that is used for finding a set of solutions which are sub-optimal under the viewpoint of the "mean scenario" load conditions, and which are submitted to a sensitivity analysis for the load uncertainty. This paper presents a further development of the algorithm presented in [1], employing now a memetic algorithm (an algorithm endowed with local search operators) instead of the original immunological algorithm. The new algorithm is shown to present a better behavior, achieving a better set of candidate solutions, which dominate the solution set of the former algorithm. The solution set of the proposed algorithm is also stable, in the senses that: (i) the same set of solutions is found systematically;and (ii) the merit function values associated to those solutions vary smoothly from one solution to another one. It can be concluded that the design procedure proposed in [1] should be performed preferentially with the algorithm proposed here.
机译:最近的一篇论文[1]提出了一种在配电网络设计中考虑到负载演变的不确定性的方法。该论文提出了一种免疫学算法,用于寻找在“平均情景”负载条件下次优的解决方案集,并将其提交给负载不确定性的敏感性分析。本文提出了在[1]中提出的算法的进一步发展,现在采用一种模因算法(一种赋予了局部搜索算子的算法)代替了原来的免疫学算法。新算法显示出更好的性能,获得了更好的候选解决方案集,这些候选解决方案主导了以前算法的解决方案集。在以下意义上,所提出算法的解决方案集也是稳定的:(i)系统找到同一套解决方案;以及(ii)与这些解决方案相关的优值函数值在一个解决方案之间逐渐变化。可以得出结论,在[1]中提出的设计程序应该优先使用此处提出的算法来执行。

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