To enable an in-depth study of active cyber-physical distribution network, a cyber subsystem model is urgently needed to describe the performance in distribution communication. The methods for quantifying the interactions between subsystems, especially indirect interactions, have not been adequately studied in the existing research. In this paper, a novel model is developed to evaluate the validity of cyber link considering dynamic routing, delay, and communication error, particularly the cyber traffic. Then, an analytical method is presented to quantify the impact of cyber faults considering the functionality validity during distribution automation. And the reliability of cyber and physical subsystems is evaluated based on Non-Sequential and Sequential Monte Carlo methods respectively. Finally, a test system for reliability evaluation is established to analyze the influences of cyber faults. Also sensitivity analyses on the impact of cyber network traffic, element failure rate, and network topology and access communication technology are carried out. The obtained results could provide useful insights into planning and operation of active cyber-physical distribution networks.

As the number and capacity of photovoltaic (PV) power stations increase, it is of great significance to evaluate the PV-connected power systems in an effective, reasonable, and quick way. In order to overcome the challenge of PV’s time-sequential characteristic and improve upon the computational efficiency, this paper presents a new methodology to evaluate the reliability of the power system with photovoltaic power stations, which combines intelligent state space reduction and a pseudo-sequential Monte Carlo simulation (PMCS). First, a non-aggregate Markov model of photovoltaic output is established, which effectively retains some time-sequential representation of the PV output. Then, the differential evolution algorithm (DE) is introduced into the sampling stage of PMCS to carry out an intelligent state space reduction (ISSR). By using the DE algorithm, success states are searched out and removed, thus the state space is reduced and formed with a high density of loss-of-load. Hence, unnecessary samplings are avoided, which optimizes the PMCS sampling mechanism and improves the computational efficiency. Finally, the proposed method is tested in the modified IEEE RTS-79 system. The results indicate that this new method has a better computational efficiency than the time-sequential Monte Carlo simulation method (TMCS) and pure PMCS. In addition, the effectiveness and feasibility of this method are also verified.

With the growing study on the active distribution network, an objective and efficient reliability evaluation method for such cyber-physical systems (CPS) is urgently needed. In this paper, first considering the cyber transmission performance, a new method is proposed for efficient evaluation of cyber link validity based on frequency-time domain transformation. In order to quantify the indirect interdependencies of cyber failures, an unresponsiveness probability model for switches is established. Then, an innovative method is proposed by combining the equivalent method and the minimal path method. Finally, a test system is established to verify the effectiveness of the proposed method. This study is instrumental in informing the efficient planning of contemporary CPS-based distribution networks.