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首页> 外文期刊>Electric power systems research >Optimal allocation of capacitors in unbalanced multi-converter distribution systems: A comparison of some fast techniques based on genetic algorithms
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Optimal allocation of capacitors in unbalanced multi-converter distribution systems: A comparison of some fast techniques based on genetic algorithms

机译:不平衡多转换器配电系统中电容器的最佳分配:基于遗传算法的一些快速技术的比较

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摘要

Genetic algorithms (GAs) are widely used for optimal allocation of capacitors in distribution systems. When dealing with large-scale systems, such as in case of unbalanced multi-converter distribution systems, these algorithms can require significant computational efforts, which reduce their effectiveness. In order to reduce processing time for GAs and simultaneously maintain adequate levels of accuracy, methods based on the reduction of the search space of GAs or based on micro-genetic algorithms have been proposed. These methods generally guarantee good solutions with acceptable levels of computational effort. In this paper, some fast, GA-based methods are compared and applied for solving the problem of optimal sizing and siting of capacitors in unbalanced multi-converter distribution systems. The algorithms have been implemented and tested on the unbalanced IEEE 34-bus test distribution system, and their performances have been compared with the performance of the simple genetic algorithm technique.
机译:遗传算法(GA)被广泛用于配电系统中电容器的最佳分配。当处理大型系统时,例如在不平衡的多转换器配电系统的情况下,这些算法可能需要大量的计算工作,从而降低了其有效性。为了减少GA的处理时间并同时保持足够的精度水平,已经提出了基于GA的搜索空间减少或基于微遗传算法的方法。这些方法通常可以保证良好的解决方案以及可接受的计算水平。在本文中,比较了一些基于遗传算法的快速方法,并将其用于解决不平衡多转换器配电系统中电容器的最佳尺寸和选址问题。该算法已在不平衡的IEEE 34总线测试分配系统上实现和测试,并将其性能与简单遗传算法技术的性能进行了比较。

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