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Efficient Identification Method for Power Line Outages in the Smart Power Grid

机译:智能电网中电力线中断的有效识别方法

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摘要

This paper considers the use of phasor angle measurements provided by phasor measurement units to identify multiple power line outages. The problem of power line outage identification has traditionally been formulated as a combinatorial optimization problem, the optimal solution of which can be found through an exhaustive search. However, the size of the search space grows exponentially with the number of outages and may thus pose a potential problem for the practical implementation of an exhaustive search, especially when multiple power line outages are considered in a power system. To reduce the complexity while improving outage detection performance, we propose a novel global stochastic optimization technique based on cross-entropy optimization, which has been proven to be a powerful tool for many combinatorial optimization problems, to identify multiple line outages. To validate the effectiveness of the proposed approach, the algorithm is tested using IEEE 118- and 300-bus systems, as well as a Polish 2736-bus system. Simulation results demonstrate that the percentage of correctly identified line outages achieved by the proposed method outperforms those obtained by existing sparse signal recovery algorithms.
机译:本文考虑了使用由相量测量单元提供的相量角测量来识别多条电源线中断。传统上,将电力线中断识别问题描述为组合优化问题,可以通过详尽搜索找到其最佳解决方案。但是,搜索空间的大小随中断次数呈指数增长,因此可能对穷举搜索的实际实现造成潜在的问题,尤其是在电源系统中考虑多条电源线中断的情况下。为了降低复杂度,同时提高停电检测性能,我们提出了一种基于交叉熵优化的新型全局随机优化技术,该技术已被证明是解决许多组合优化问题,识别多条线路停电的有力工具。为了验证所提出方法的有效性,使用IEEE 118总线和300总线系统以及波兰2736总线系统对算法进行了测试。仿真结果表明,所提出的方法可正确识别线路中断的百分比优于现有的稀疏信号恢复算法所获得的百分比。

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