Computational analysis of cascading failures in power networks

Computational analysis of cascading failures in power networks
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电网连锁故障的计算分析

DOI:
10.1145/2465529.2465752
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发表时间:
2013
期刊:
Proceedings of the 24th International Conference on World Wide Web
影响因子:
--
通讯作者:
G. Zussman
G. Zussman
中科院分区:
--
文献类型:
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作者:
Dorian Mazauric;Saleh Soltan;G. Zussman

文献摘要

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本文主要研究电网输电系统中的级联线路故障。这种级联不仅对电网,而且对相互连接的通信网络都可能造成毁灭性的影响。最近的大规模停电表明,基于流行病和渗漏的工具在级联进化建模方面存在局限性。因此,基于线性化的功率流模型(与经典的包流模型有很大的不同),我们得到了关于级联的各种特性的结果。具体来说,我们考虑诸如故障之间的距离、级联的长度以及级联后满足的需求(负载)的比例等性能指标。例如,我们表明,由于模型的独特属性:(i)后续故障之间的距离可以任意大,级联可以任意长,(ii)一组大的初始线路故障可能比一组线路故障的影响要小,(iii)网络参数的微小变化可能会产生重大影响。此外,我们表明,找到其删除具有最显著影响的线集(在各种指标下)是NP-Hard的。此外,我们还开发了一种快速算法来重新计算串级的每一步流。研究结果可以为智能电网测量和控制算法的设计提供见解,以减轻级联。
This paper focuses on cascading line failures in the transmission system of the power grid. Such a cascade may have a devastating effect not only on the power grid but also on the interconnected communication networks. Recent large-scale power outages demonstrated the limitations of epidemic- and percolation-based tools in modeling the cascade evolution. Hence, based on a linearized power flow model (that substantially differs from the classical packet flow models), we obtain results regarding the various properties of a cascade. Specifically, we consider performance metrics such as the the distance between failures, the length of the cascade, and the fraction of demand (load) satisfied after the cascade. We show, for example, that due to the unique properties of the model: (i) the distance between subsequent failures can be arbitrarily large and the cascade may be arbitrarily long, (ii) a large set of initial line failures may have a smaller effect than a failure of one of the lines in the set, and (iii) minor changes to the network parameters may have a significant impact. Moreover, we show that finding the set of lines whose removal has the most significant impact (under various metrics) is NP-Hard. Moreover, we develop a fast algorithm to recompute the flows at each step of the cascade. The results can provide insight into the design of smart grid measurement and control algorithms that can mitigate a cascade.