A new approach for reliability assessment of the smart microgrids using k-shortest path algorithms

The reliability of cyber-physical microgrids (MGs) is crucial in the development of smart grids. The reliability of MGs can be affected by cyber network failures, which have a significant impact on the physical components. Since MGs have interdependent cyber and physical elements, a smart MG can be viewed as a system of n dependent two-mode components. This paper proposes an approach to finding the k most likely configurations of the system. The method involves three phases. Firstly, the multi-mode model is obtained for physical components, considering the operation and topology of the cyber network. Then, the problem is transformed to finding the k most likely state of a system consisting of n independent multi-mode components. In the second phase, a transformation using new transformed metrics is applied. This results in the problem being converted to finding the k shortest path, which can be solved using efficient algorithms. Finally, the states are evaluated using a DC load flow, and reliability indices such as loss of load probability (LOLP) and expected energy not supplied (EENS) are calculated. Moreover, we have incorporated the dynamic thermal rating (DTR) system into our proposed model, addressing the safe enhancement of system component ratings. The results indicate that the most probable states of the system are related to the failure of distribution generators. The most severe events occur due to failure in the cyber network, and cyber network malfunction has a higher effect on EENS compared to LOLP. Additionally, we observe a significant enhancement in reliability indices when considering the DTR system over the static thermal rating (STR) system.This approach is efficient in reliability calculation using fewer system states.