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Reliability Analysis of Bulk Power Systems Using Swarm Intelligence

机译:使用群体智能的散装电力系统可靠性分析

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This paper documents research into the use of an adaptive cultural model and collective intelligence as a means of characterizing the reliability of bulk power networks. Historically, utilities support the reliable design and operation of bulk power networks through first-order contingency analysis. In contingency analyses the list of candidate elements for disruption are identified by engineers a priori based on the rate at which the elements failure through the course of normal grid operation. The new method, an implementation of particle swarm analysis, a swarm of 'virtual power engineers' successfully identified the set of network elements which, if disrupted, would possibly lead to a cascading series of events resulting in the most wide spread damage. The methodology is technology independent: it can be applied on not only for reliability analysis of bulk power systems, but also other energy systems or transportation systems. The methodology is scale neutral: it can be applied to power distribution networks at the local, state or regional level.
机译:本文文件研究了自适应文化模型和集体智能的使用,作为表征散装电网可靠性的手段。从历史上看,公用事业公司通过一阶试点分析支持批量电网的可靠设计和操作。在意外情况下,分析中断的候选元素清单是通过工程师来认证的,这是基于通过普通网格运行过程的元素故障的速率来确定。新方法,粒子群分析的实现,一群'虚拟电力工程师'成功识别了一组网络元素,如果中断,可能导致级联事件,导致最广泛的传播损坏。该方法是技术独立:它不仅可以应用于散装电力系统的可靠性分析,还可以应用其他能源系统或运输系统。该方法是中立的尺度:它可以应用于当地,州或区域层面的配电网络。

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