A High-Resolution and High-Efficiency Distribution Network State Estimation Framework Based on Micro-PMU Data

The increasing penetration of renewable energy into distribution networks makes it necessary for the distribution system operator to monitor the state of distribution networks in real time. However, traditional measurement devices in distribution networks cannot provide high-resolution data. Thanks to the installation of micro-PMUs, high-resolution voltage and power measurement data at several points in a distribution network are available. In this paper, a framework which uses high-resolution micro-PMU data and low-resolution smart meter data to perform real-time state estimation in distribution networks is proposed. A distribution network is partitioned by the micro-PMUs into multiple zones, and micro-PMU measurement data are used to detect and locate sharp power change in each zone. When sharp power changes do not occur, the state of a zone can be tracked with the linearized measurement equations. When a sharp power change occurs, state estimation is performed by iterations, and the optimal initial values for the iterations are generated based on the location and magnitude of the power change. Case studies demonstrate the computational efficiency and the robustness of the proposed state estimation framework.