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A Parallel Bees Algorithm for ATC Enhancement in Modern Electrical Network

机译:现代电网ATC增强的平行蜜蜂算法

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This paper presents a parallel-based methodology for placement of Flexible AC Transmission Systems (FACTS) devices in order to reduce the time it takes to reach a solution while maximizing the available transfer capability (ATC) of a given power system. The Parallel Bees Algorithms (PBA) simultaneously searches the location, size and types of FACTS devices to enhance ATC between the source and sink area. Four types of emerging FACTS devices are used namely; Thyristor Controlled Series Compensator (TCSC), Static Var Compensator (SVC), Unified Power Flow Controller (UPFC) and Thyristor Controlled Phase Shift Tranformer (TCPST). The IEEE118 Bus system is used to illustrate the applicability of the proposed algorithm to enhance ATC effectively. The results obtained are very encouraging and compared to a Bees Algorithm (BA), Genetic Algorithm (GA) and Parallel Genetic Algorithms (PGA). The results show that parallel computing technique can be used effectively to reduce time to reach a solution for large scale network and FACTS devices have proven their utility for ATC improvement.
机译:本文礼物,以减少它需要同时最大化给定的电力系统的可用输电能力(ATC),以达成解决方案的时候了柔性交流输电系统(FACTS)设备的放置基于并行的方法。并行蜜蜂算法(PBA)同时搜索的位置,大小和类型的FACTS装置来源和宿区域之间提高ATC。四种新兴的FACTS装置被使用,即;可控串联补偿器(TCSC),静止无功补偿器(SVC),统一潮流控制器(UPFC)和可控相移变压(TCPST)。在IEEE118总线系统被用来说明所提出的算法的适用性有效地提高ATC。获得非常令人鼓舞的,相比于蜜蜂算法(BA),遗传算法(GA)和并行遗传算法(PGA)的结果。结果表明,并行计算技术可以有效地用于减少的时间来达到大规模网络和FACTS设备的解决方案已经证明了它们对改善ATC效用。

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