Distributed Multi-Area State Estimation for Power Systems with Switching Communication Graphs

We consider distributed multi-area state estimation algorithms for power systems with switching communication graphs. The power system is partitioned into multiple geographically non-overlapping areas and each area is assigned with an estimator to give a local estimate of the entire power system's state. The inter-area communication networks are assumed to switch among a finite set of digraphs. Each area runs a distributed estimation algorithm based on consensus+innovations strategies.By the binomial expansion of matrix products, time-varying system and algebraic graph theories, we prove that all area's local estimates converge to the global least square estimate with probability1 if the measurement system is jointly observable and the communication graphs are balanced and jointly strongly connected. Finally, we demonstrate the theoretical results by an IEEE 118-bus system.