Real-Time Topology Detection and State Estimation in Distribution Systems Using Micro-PMU and Smart Meter Data

Topology detection and state estimation in real-time are critical for modern distribution systems management and control. However, the number of sensors in distribution networks is limited, and communication links between switch devices and distribution management system are not well-established. In this regard, this article proposes mixed-integer quadratic programming formulations to determine the topology of distribution network and estimate distribution system states simultaneously using micro-phasor measurement units and smart meter data. Two approaches based on ac optimal power flow are proposed and analyzed: polar power-voltage (PPV) formulation and rectangular current-voltage (RIV) formulation. The proposed models can identify multiple simultaneous switching actions and different topology configurations including radial and meshed networks. Only measurement data at each time interval are needed to identify the topology and states of the system correctly. The proposed models are tested on a modified IEEE-33 bus system with realistic load data from the Pecan Street Inc. database and a real distribution feeder of an electric utility. The results confirm that both models can identify system topology and states with remarkable accuracy in real-time, whereas the RIV model outperforms the PPV model. Moreover, the impact of missing data on the performance of the model is evaluated.