Analytical reliability assessment of cyber-physical distribution system with distributed feeder automation

Abstract

Cyber-physical distribution system (CPDS) handles power grid faults by feeder automation. The reliability assessment of CPDS has been intensively discussed for centralized feeder automation (CFA) in existing researches. However, the inapplicability of CFA reliability models, and the low computation efficiency issue of the mostly used Monte Carlo method greatly limits their application in practical engineering cases of the large-scale CPDS with the distributed feeder automation (DFA) mode. Thus, this paper proposes a region-based analytical reliability assessment method for DFA, which has high computation efficiency in the large-scale CPDS. Firstly, the reliability impacts of cyber system anomalies in the DFA mode are analysed and the cyber reliability models are built considering both cyber device failures and cyber-attacks. Then, the cyber system status is integrated into malfunction probability modelling of switches for reliability assessment. Finally, the load reliability is assessed based on the fault region division by the proposed analytical method and the reliability indices are calculated. The accuracy, efficiency and scalability of the proposed method are verified in case studies.