Distribution System State Estimation Using the Hamiltonian Cycle Theory

Since the origin of energy management systems, state estimation applications have aided in automatic power system operations, mainly for transmission systems. Currently, however, smart grid concepts are modifying the behavior of distribution systems through a rapid increase of controllable distributed generators, demand response, and electric vehicles. Consequently, the advanced metering infrastructure is providing a large amount of synchronized metering data with high accuracy and resolution, which favors the development of state estimation procedures to sustain distribution management systems.

Therefore, this paper presents the formulation of a novel algorithm for state estimation solution in distribution networks using the Hamiltonian cycle theory, where the networkstates are quickly obtained through a calculation scheme under the normal operating conditions.

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