基于实时量测与滑动时间窗策略的配电网运行方式动态追踪

The traditional topology tracking methods of distribution network do not fully consider the diversity of power flow and the complexity of low-voltage working conditions in distribution network，and thus have the problem of weak engineering applicability. To this end，a data-driven method is proposed to track and verify the operation modes of distribution network using real-time measurement. Based on the spatio-temporal operation characteristics of distribution network，a technical path based on critical path and boundary segment analysis is proposed. A diagnosis framework of two-stage operation mode adjustment based on sliding time window is constructed. Firstly，the dynamic monitoring of boundary segments is conducted，and the CatBoost classifier is used to diagnose features such as power and voltage to identify the transfer behaviors. Then，the feeder topology is traversed in reverse to aggregate the upstream transfer segments，so as to clarify the transfer segments and update the dynamic topology. Through horizontal comparison，the reasonable configuration of sliding time window and diagnosis time delay is obtained，and at the same time，the superiority of the CatBoost classification algorithm in terms of performance is proved. The experimental results show that the proposed method can accurately achieve the dynamic tracking of distribution network operation mode and achieve a good balance in terms of accuracy and timeliness.