电力安全是现代社会持续发展的重要保障.随着信息技术逐步发展,网络攻击手段的日渐增多和变强会对新型电力系统造成严重破坏,而合理的网络拓扑结构和有效的网络防御资源的是电力系统遭受网络攻击后负荷恢复的关键.为此,提出一种虚假数据注入(false data injection attack,FDIA)-蠕虫混合攻击下的配电网信息物理系统(cyber-physical systems,CPS)弹性拓扑优化和防御资源配置策略,用于提高配电系统网络攻击下的弹性.该模型采用上、中、下3层的框架对拓扑结构和防御资源进行优化:上层建立以规划成本和失负荷风险为目标的多目标帕累托规划模型,结合中层计及攻击与恢复的网络攻击传播模型,采用非支配排序遗传算法-Ⅱ(non-dominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)进行规划方案求解;下层考虑信息层与物理层的多种耦合方案,基于配电网CPS弹性度量指标对拓扑优化配置进行评估.与传统的一对一串联模式方案相比,通过模型求解的3种耦合关系下的网络拓扑结构与防御资源优化方案,在提高系统弹性方面能够发挥重要作用.
Resilient topology optimization on cyber-physical system of distribution networks under FDIA-Worm hybrid attacks
Power security is a crucial guarantee for the sustainable development of modern society. With the gradual development of information technology,the increasing number and strength of cyber attack methods can cause severe damage to new power systems. Reasonable network topology and effective network defense resources are key to load recovery after a power system suffers a cyber attack. Therefore,a strategy for resilient topology optimization and defense resource allocation of the cyber-physical system (CPS) of distribution networks under FDIA-Worm hybrid attacks is proposed to enhance the resilience of distribution systems against cyber attacks. This model adopts a three-tier framework of upper,middle,and lower levels to optimize the topology and defense resources:the upper level establishes a multi-objective Pareto planning model with planning costs and load loss risks as objectives,combines it with the middle-level network attack propagation model that considers attacks and recovery,and uses the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) to solve the planning scheme;the lower level considers various coupling schemes between the information layer and the physical layer,and evaluates the optimal topology configuration based on resilience metrics of the CPS of distribution networks. Compared with traditional one-to-one series mode schemes,the optimized network topology and defense resource schemes under the three coupling relationships obtained through model solution can play a significant role in enhancing system resilience.
resiliencecyber-physical system for distribution networksnetwork topology optimizationmultiobjective Pareto programmingmulti-stage resilience metrics
万方数据
维普
