College of Computer, National University of Defense Technology, Changsha 410073, China.
Department of Electronic Information and Electrical Engineering, Changsha University, Changsha 410022, China.
Sensors (Basel). 2018 May 24;18(6):1699. doi: 10.3390/s18061699.
Many previous works only focused on the cascading failure of global coupling of one-to-one structures in interdependent networks, but the local coupling of dual coupling structures has rarely been studied due to its complex structure. This will result in a serious consequence that many conclusions of the one-to-one structure may be incorrect in the dual coupling network and do not apply to the smart grid. Therefore, it is very necessary to subdivide the dual coupling link into a top-down coupling link and a bottom-up coupling link in order to study their influence on network robustness by combining with different coupling modes. Additionally, the power flow of the power grid can cause the load of a failed node to be allocated to its neighboring nodes and trigger a new round of load distribution when the load of these nodes exceeds their capacity. This means that the robustness of smart grids may be affected by four factors, i.e., load redistribution, local coupling, dual coupling link and coupling mode; however, the research on the influence of those factors on the network robustness is missing. In this paper, firstly, we construct the smart grid as a two-layer network with a dual coupling link and divide the power grid and communication network into many subnets based on the geographical location of their nodes. Secondly, we define node importance ( N I ) as an evaluation index to access the impact of nodes on the cyber or physical network and propose three types of coupling modes based on N I of nodes in the cyber and physical subnets, i.e., Assortative Coupling in Subnets (ACIS), Disassortative Coupling in Subnets (DCIS), and Random Coupling in Subnets (RCIS). Thirdly, a cascading failure model is proposed for studying the effect of local coupling of dual coupling link in combination with ACIS, DCIS, and RCIS on the robustness of the smart grid against a targeted attack, and the survival rate of functional nodes is used to assess the robustness of the smart grid. Finally, we use the IEEE 118-Bus System and the Italian High-Voltage Electrical Transmission Network to verify our model and obtain the same conclusions: (I) DCIS applied to the top-down coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or ACIS, (II) ACIS applied to a bottom-up coupling link is better able to enhance the robustness of the smart grid against a targeted attack than RCIS or DCIS, and (III) the robustness of the smart grid can be improved by increasing the tolerance α . This paper provides some guidelines for slowing down the speed of the cascading failures in the design of architecture and optimization of interdependent networks, such as a top-down link with DCIS, a bottom-up link with ACIS, and an increased tolerance α .
许多先前的工作仅关注于相依网络中一对一结构的全局耦合级联失效,但由于其复杂的结构,双耦合结构的局部耦合很少被研究。这将导致一个严重的后果,即在双耦合网络中,许多一对一结构的结论可能是不正确的,并且不适用于智能电网。因此,非常有必要将双耦合链路细分为自上而下的耦合链路和自下而上的耦合链路,以便通过结合不同的耦合模式来研究它们对网络鲁棒性的影响。此外,电网的功率流会导致故障节点的负载分配给其相邻节点,并在这些节点的负载超过其容量时引发新一轮的负载分配。这意味着智能电网的鲁棒性可能受到四个因素的影响,即负载重新分配、局部耦合、双耦合链路和耦合模式;然而,对这些因素对网络鲁棒性的影响的研究是缺失的。在本文中,我们首先构建了一个具有双耦合链路的两层智能电网网络,并根据节点的地理位置将电网和通信网络划分为多个子网。其次,我们定义节点重要性(NI)作为评估指标,以评估节点对网络的物理或网络的影响,并基于物理子网和网络子网中的节点的 NI 提出了三种类型的耦合模式,即子网中的聚集耦合(ACIS)、子网中的去聚集耦合(DCIS)和子网中的随机耦合(RCIS)。然后,提出了一种级联失效模型,用于研究双耦合链路的局部耦合与 ACIS、DCIS 和 RCIS 相结合对智能电网抵御有针对性攻击的鲁棒性的影响,并使用功能节点的存活率来评估智能电网的鲁棒性。最后,我们使用 IEEE 118 母线系统和意大利高压输电网验证了我们的模型,并得到了相同的结论:(I)应用于自上而下的耦合链路的 DCIS 比 RCIS 或 ACIS 更能提高智能电网对有针对性攻击的鲁棒性,(II)应用于自下而上的耦合链路的 ACIS 比 RCIS 或 DCIS 更能提高智能电网对有针对性攻击的鲁棒性,以及(III)通过增加容忍度 α 可以提高智能电网的鲁棒性。本文为在架构设计和相依网络的优化中减缓级联失效的速度提供了一些指导,例如具有 DCIS 的自上而下的链路、具有 ACIS 的自下而上的链路和增加的容忍度 α 。