Abstract-This paper proposes a data-driven approach to detect the switching actions and topology transitions in distribution networks. It is based on the real time analysis of time-series voltages measurements. The analysis approach draws on data from high-precision phasor measurement units (µPMUs or synchrophasors) for distribution networks. The key fact is that timeseries measurement data taken from the distribution network has specific patterns representing state transitions such as topology changes. The proposed algorithm is based on comparison of actual voltage measurements with a library of signatures derived from the possible topologies simulation. The IEEE 33-bus model is used for the algorithm validation.
A data-driven online algorithm is proposed in REF for detecting a switching event by comparing a trend vector built from μPMU data with a given library of signatures derived from the possible topology changes.
Data-Driven Approach for Distribution Network Topology Detection
2015 IEEE Power & Energy Society General Meeting
2015 IEEE Power & Energy Society General Meeting
Mathematics Computer Science