A Dependency Analysis Model for Resilient Wide Area Measurement Systems in Smart Grid

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.