A Model for Robust Distributed Hierarchical Electric Power Grid State Estimation

State estimation is a key problem wherever systems can only be observed partially, and is typically a prerequisite for effective control. The most widespread current use of state estimation is in electrical power networks, which combine distribution over wide areas with real-time requirements. A number of state estimators have been proposed, but studies of robustness against attacks has concentrated solely on the centralised case; here we discuss the hierarchical case particularly relevant for smart and micro-grid environments. Existing models are too coarse to provide the necessary insight to understand the robustness to different, also novel, types of attacks. These have so fare been studied only for centralised approaches, and are also relatively coarse in the forced states investigated. In this paper we therefore describe a multi-level hierarchical state estimator capable of describing sub-networks linked by tie-lines with minimal overlapping areas criteria, placing particular emphasis on the ability to achieve rapid algorithm convergence, also reporting on simulative validation of our results.