Smart grids: Challenges of processing heterogeneous data for risk assessment

Recent advances in IT-related fields are opening up a broad range of novel applications. This is especially true in the energy sector, where Smart Grid solutions are offering new opportunities for the monitoring of power transmission and distribution in electrical grids. However, optimal use of potentially accessible data sources is challenging, and most of the current Smart Grid projects continue to exhibit suboptimal utilization of heterogeneous information. This situation is also faced when it comes to the assessment of risks associated to operation of electricity transmission and distribution networks. As a consequence, current management systems fail to provide accurate estimations of risk levels in real-world situations. Our paper addresses this issue and contributes to the identification of possible solutions. The paper identifies a number of heterogeneous data sources which could be relevant for risk assessment, but which are currently not fully exploited. Furthermore, the paper points to valuable relations existing across these data sources, that promote a better understanding of real-world situations and empower a more accurate analysis of well-known or newly identified risks within the framework of Smart Grids.