Bi-Level Resilient Control Solution for Distributed Feeder Automation System Under Hybrid Attack

Abstract

Distributed feeder automation system (DFAs), as a promising protection technology for power distribution system (PDS) with distributed generation, its vulnerability to cyberattacks and hybrid attacks (contains both physical and cyberattacks) is gradually recognized and haunts utilities, creating potential risks for its large-scale applications. This paper proposes a novel bi-level resilient control solution (BRCS) deployed to DFAs without hardware burden. Two key modules are developed: 1) Lightweight distributed cyberattack detection module (DCDM), deployed into agents of DFAs, based on unsupervised learning to realize the quick detection and reporting of cyberattacks; 2) Robust centralized fault section localization module (CFSLM), installed in DFAs’ host workstation located in control center, achieving the correctly fault section localization and the high dimensionally awareness of attack events in cyberattack and hybrid attack scenarios. By adopting BRCS, outages and load losses caused by cyberattacks can be 100% avoided, and faults caused by physical attacks can be correctly isolated at once. Finally, the effectiveness and performance of the proposal are verified and conducted by the real two-feeder test platform with DFAs. In this process, a digital high-dimensional awareness and control unit is created against cyber and hybrid attacks, contributing to the system-level application of risk management and resilient control.