Graph Propagation and Distributed State Estimation Based on Local Modeling

We present a novel algorithm for distributed state estimation in power systems, based on graph theory and exchange of information between nodal entities in combination with local non-Jacobian based modeling. The bus-based power balance equations are used to generate a successively better estimate based on locally available data only, which is then sent out to adjacent graph vertices, so that information travels even to parts of the network that have fewer data collected. For this reason, full power system observability is not required, and this procedure could be applied even if parts of the system lack needed measurements. To demonstrate the effectiveness and scalability of the proposed algorithm, it is applied to both 14-bus and 300-bus test systems.