Topology Tracking for Active Distribution Networks

With the integration of intermittent renewable energy sources in the distribution network, the number of network reconfiguration events has increased significantly. In a medium voltage distribution network, most of the critical circuit breakers' (CBs') statuses are monitored by remote terminal units (RTUs). However, in many cases, some of the CBs' status may not be correctly updated by the supervisory control and data acquisition (SCADA) system because of communication failure and data packet loss issues. Thus, the distribution system operator (DSO) cannot solely rely on CB status provided by the SCADA for topology detection. This paper proposes a data-driven topology tracking algorithm for active distribution networks. The topology of the distribution network is represented with a time-varying connectivity matrix. The changes in network topology are detected by estimating the elements of the bus connectivity matrix using voltage phase angle measurements provided by a sparse set of micro phasor measurement units (mu PMUs). The algorithm extracts information from previous network topology using an l(1) norm regularization on the difference of consecutive connectivity matrices. The changes in topology can be detected by observing a few mu PMUs phasor samples. The algorithm is tested on IEEE benchmark test feeders with real load profiles.

Automated summary

This paper proposes a data-driven topology tracking algorithm for active distribution networks to address the issue of topology detection caused by communication failure and data packet loss in distribution networks. The algorithm utilizes l(1) norm regularization and sparse mu PMUs phasor samples to detect changes in network topology.