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A Recursive Bayesian Approach for Identification of Network Configuration Changes in Distribution System State Estimation

This paper proposes a new approach for tackling the notoriously difficult problem of network topology identification based on outputs of state estimation. It furnishes topology identification schemes that are computationally inexpensive as the rejection rate of incorrect network topologies is exponential, permitting analysis of a very large number of candidate network topologies. The proposed methodology opens new opportunities for the implantation of real-time control of large-case distribution networks in which measurements are only available at the main substation and the topology status is not monitored. This work provided input to EPSRC grants EP/K006274/1 (£1m) and EP/K036327/1 (£1.2m).