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Fault identification based on artificial immunological systems

机译:基于人工免疫系统的故障识别

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The growing tendency in the number of distributed generation units, directly connected at the distribution level, inevitably brings a number of new challenges. One of the effects is that this new topology may influence the performance of analysis methods and techniques that were based on traditional systems. Fault location methods in distribution systems are examples of how inserting of new generation sources can change the efficiency of these tools. Considering that fault location is a fundamental step to help distribution companies to maintain reliability indices within acceptable margins, this work presents a method applicable to both traditional systems and systems with the presence of distributed generators. In order to achieve this goal, a methodology was developed based on artificial immunological systems technique, which is generally used to complex problems-solving. The methodology evaluated considering several scenarios in the test system and presented a satisfactory performance, being able to estimate characteristics such as location, fault type and fault resistance in an efficient way. (C) 2017 Elsevier B.V. All rights reserved.
机译:在配电级直接连接的分布式发电单元数量的增长趋势不可避免地带来了许多新的挑战。影响之一是这种新的拓扑结构可能会影响基于传统系统的分析方法和技术的性能。配电系统中的故障定位方法是如何插入新一代电源可以改变这些工具效率的示例。考虑到故障定位是帮助配电公司将可靠性指标保持在可接受范围内的基本步骤,这项工作提出了一种适用于传统系统和存在分布式发电机的系统的方法。为了实现这一目标,基于人工免疫系统技术开发了一种方法,通常用于解决复杂的问题。该方法在测试系统中考虑了多种情况进行了评估,并表现出令人满意的性能,能够以有效的方式估算位置,故障类型和故障电阻等特性。 (C)2017 Elsevier B.V.保留所有权利。

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