Nodal reliability evaluation of impact of hurricanes on transmission and distribution systems

Adverse weather such as hurricanes can have a significant impact on power system reliability. More accurately predicting the impact of hurricanes on power systems can help utilities to be better prepared for upcoming hurricanes. Nodal reliability indices are important for allocating resources to the different parts of the power system. In this paper, a fuzzy inference system (FIS) built by using fuzzy c-mean clustering is combined with minimal cut-set method to compute the nodal reliability indices of transmission systems during hurricane duration. Here, FIS is used to map the nonlinear functional relationship between hurricane parameters and the increment multipliers of the failure rates (IMFR) of transmission lines. Moreover, the extension of the proposed method and the application of these indices to distribution systems are discussed. The proposed method is applied to the modified IEEE Reliability Test System (RTS). The implementation demonstrates that the proposed method is effective and efficient and is flexible in applications.