Flexible and robust communication-assisted protection strategy for distribution networks based on comprehensive feature recognition

Remedial countermeasures are introduced by communication-assisted protection (CAP) to cope with the impacts of insufficient sampling configurations on distribution network (DN) protection. To promote the flexibility of CAP applications and the robustness of CAP performance, a comprehensive feature recognition-based CAP (CFRCAP) strategy retaining the advantages of the feature recognition method and the protective relay deployment in fault detection is proposed in this paper. State features are calculated from state estimation methods and adopted as complementary inputs in protective relays. In turn, relay features generated by the protective relays are employed in the process of feature recognition together with the calculated state features. Therefore, both the sampling resources and the protective relay resources are fully utilized. Different fault scenarios are screened to perform fault diagnosis and location. Cases of a general sampling configuration and cases with issues of lack and loss of samplings are investigated to demonstrate that the proposed strategy can flexibly adapt to different sampling conditions and make optimal decisions to mitigate the impacts of sampling issues.