考虑信息物理融合的电网脆弱社团评估方法

发布时间：2018-05-24 19:58

本文选题：信息物理融合系统 + 相互依存网络　；参考：《电力自动化设备》2017年12期

【摘要】：针对目前元件级的电力信息物理脆弱性评估应用于实际大规模电力信息物理网时存在计算复杂度高和脆弱性保护配置难的问题,充分考虑网络的介观局域特征和社团结构,提出了一种考虑信息物理融合的电网脆弱社团评估方法。以电力系统潮流为边权重,采用Fast Unfolding算法对电网进行社团划分,根据电网和通信网对应分层分区建设的现状和实际耦合关系划分通信网社团,IEEE标准算例的仿真结果证明所采用社团划分方法的优越性。在不同的社团内部耦合关系下采用不同的攻击策略攻击电网中各个社团,根据整个信息物理融合系统故障后的最大连通子集指标评估电网中的脆弱社团,符合我国电网和通信网分层分区建设的现状,有利于减少计算复杂度和脆弱性保护模块化配置的难度。华中500 kV电网信息物理系统的仿真结果证明了所提方法的可行性。
[Abstract]:In order to solve the problems of high computational complexity and difficult configuration of vulnerability protection when the component level vulnerability assessment of power information physics is applied to practical large-scale power information physical network, the mesoscopic local features and community structure of the network are fully considered. In this paper, a method for evaluating vulnerable communities in power grid considering physical fusion of information is proposed. Taking power flow as the edge weight, the Fast Unfolding algorithm is used to divide the power network community. According to the current situation and the actual coupling relation of the construction of the corresponding hierarchical partition between the power network and the communication network, the simulation results of the IEEE standard example of the communication network show the superiority of the proposed method. Different attack strategies are used to attack each community in the power network under different coupling relationships within the community. The vulnerable communities in the power network are evaluated according to the maximum connected subset index of the whole information physical fusion system after failure. In line with the present situation of power network and communication network construction in China, it is helpful to reduce the computational complexity and the difficulty of modularized configuration of vulnerability protection. The simulation results of the information physical system of 500 kV power network in central China show the feasibility of the proposed method.
【作者单位】：武汉大学电气工程学院;
【基金】：国家自然科学基金资助项目(51477121)~~
【分类号】：TM73

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