Wide Area Measurement Systems (WAMSs) are used in power networks to improve the situational awareness of the operator, as well as to facilitate real-time control and protection decisions. In WAMSs, Phasor Data Concentrators (PDCs) collect time-synchronized data of Phasor Measurement Units (PMUs) through the communication system, and direct it to the control center to be used in wide-area control and protection applications. Due to the dependence of WAMSs on information and communication technologies, cyber-attacks can target these systems and propagate through them, i.e., infect a greater number of components by accessing and controlling a few of them. On this basis, this paper initially develops a Learning-Based Framework (LBF) to estimate the required defense strategy to counter the propagation of cyber-attacks in WAMSs. Afterwards, through solving a linear Binary Integer Programming (BIP) problem, this paper develops a mitigation strategy to optimally reconfigure the communication network and reduce the contamination probability for critical PMUs and PDCs while maintaining the observability of the grid. The simulation results obtained from IEEE 14- and 30-bus test systems corroborate the effectiveness of the proposed LBF and communication network reconfiguration strategy in mitigating the propagation of cyber-attacks in WAMSs.

中文翻译：

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减少网络攻击在广域测量系统中的传播


广域测量系统 （WAMS） 用于电力网络，以提高操作员的态势感知能力，并促进实时控制和保护决策。在 WAMS 中，相量数据集中器 （PDC） 通过通信系统收集相量测量单元 （PMU） 的时间同步数据，并将其直接发送到控制中心，用于广域控制和保护应用。由于 WAMS 对信息和通信技术的依赖，网络攻击可以针对这些系统并通过它们传播，即通过访问和控制其中的一些组件来感染更多的组件。在此基础上，本文初步开发了一个基于学习的框架 （LBF） 来估计所需的防御策略，以对抗 WAMS 中网络攻击的传播。然后，通过解决线性二进制整数规划 （BIP） 问题，本文开发了一种缓解策略，以最佳方式重新配置通信网络并降低关键 PMU 和 PDC 的污染概率，同时保持电网的可观测性。从 IEEE 14 总线和 30 总线测试系统获得的仿真结果证实了所提出的 LBF 和通信网络重新配置策略在减轻网络攻击在 WAMS 中传播方面的有效性。