Decentralized Power System State Estimation With Reduced Inter-Area Communication

In this paper, we present a new algorithm for decentralized state estimation in multi-area power systems. The proposed method features significantly reduced communication between areas when compared to the existing gossip-based Gauss-Newton approach. We achieve this by confining gossip iterations associated with a specific state variable to only those areas which actually observe that state variable. This increases the speed of convergence of the gossip iterations, while reducing the amount of communication required for the gossip iterations to converge. We demonstrate the efficacy of our solution with simulations on the IEEE 118-bus system with different communication models.