Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
