Wide Area Measurement Systems (WAMS) consist of the measuring and the communication layers (infrastructures) of smart grids, which are used to monitor, operate and control the electrical infrastructure. Resilience is a very important requirement in smart grids, since they must be able to resist in failures at any layer, caused both by intentional attacks or unintentional events. Thus, while cost optimization is usually the most important concern when designing WAMS, increasing the resilience of the WAMS layers should also be considered as an important constraint. In this paper we propose a model for WAMS designing that takes into consideration both optimization and resilience metrics. The proposed model extends a WAMS placement optimization model by combining an optimization algorithm with a graph-based dependency analysis approach that considers the internal dependencies between the measuring and the communication WAMS layers. Based on simulation results, we show that the proposed model increases WAMS resilience by reducing the dependency levels of carefully selected nodes and/or by selectively adding measurement units and/or communication links in places indicated by the proposed algorithm. Thus, our approach can be categorized as a hybrid resilience algorithm that combines both robustness and redundancy.

中文翻译：

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智能电网中弹性广域测量系统的相关性分析模型

广域测量系统 (WAMS) 由智能电网的测量和通信层（基础设施）组成，用于监测、操作和控制电力基础设施。弹性是智能电网中非常重要的要求，因为它们必须能够抵抗任何层的故障，无论是有意攻击还是无意事件。因此，虽然在设计 WAMS 时成本优化通常是最重要的问题，但增加 WAMS 层的弹性也应该被视为一个重要的约束条件。在本文中，我们提出了一个 WAMS 设计模型，该模型同时考虑了优化和弹性指标。所提出的模型通过将优化算法与基于图的依赖分析方法相结合，扩展了 WAMS 布局优化模型，该方法考虑了测量和通信 WAMS 层之间的内部依赖关系。基于仿真结果，我们表明所提出的模型通过降低精心选择的节点的依赖性级别和/或通过在所提出的算法指示的位置有选择地添加测量单元和/或通信链路来提高 WAMS 弹性。因此，我们的方法可以归类为结合了鲁棒性和冗余性的混合弹性算法。我们表明，所提出的模型通过降低精心选择的节点的依赖性级别和/或通过在所提出的算法指示的位置有选择地添加测量单元和/或通信链路来提高 WAMS 弹性。因此，我们的方法可以归类为结合了鲁棒性和冗余性的混合弹性算法。我们表明，所提出的模型通过降低精心选择的节点的依赖性级别和/或通过在所提出的算法指示的位置有选择地添加测量单元和/或通信链路来提高 WAMS 弹性。因此，我们的方法可以归类为结合了鲁棒性和冗余性的混合弹性算法。