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State estimation in power distribution systems is a key component forincreased reliability and optimal system performance. Well understood intransmission systems, state estimation is now an area of active research indistribution networks. While several snapshot-based approaches have been usedto solve this problem, few solutions have been proposed in a dynamic framework.In this paper, a Past-Aware State Estimation (PASE) method is proposed fordistribution systems that takes previous estimates into account to improve theaccuracy of the current one, using an Ensemble Kalman Filter. Fewer phasormeasurements units (PMU) are needed to achieve the same estimation error targetthan snapshot-based methods. Contrary to current methods, the proposed solutiondoes not embed power flow equations into the estimator. A theoreticalformulation is presented to compute a priori the advantages of the proposedmethod vis-a-vis the state-of-the-art. The proposed approach is validatedconsidering the 33-bus distribution system and using power consumption tracesfrom real households.

State Estimation in Power Distribution Systems Based on Ensemble Kalman Filtering