A State-Failure--Network Method to Identify Critical Components in Power Systems
| Autor: | Li, Linzhi, Wu, Hao, Song, Yonghua, Liu, Yi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Electric Power Systems Research Volume 181, April 2020, 106192 |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1016/j.epsr.2019.106192 |
| Popis: | In order to mitigate cascading failure blackout risks in power systems, the critical components whose failures lead to high blackout risks should be identified. In this paper, such critical components are identified by the state-failure network (SF-network) formed by cascading failure chain and loss data, which can be gathered from either utilities or simulations. The failures along the chains are recombined in the SF-network, where each failure is allocated a value that can reveal the blackout risks after their occurrences. Thus, critical failures can be identified in the SF-network where the failures raise up blackout risks, and thus the critical components can be found based on their critical failure risks. The simulation results validate the effectiveness of the proposed method. Comment: Submitted to the Electric Power Systems Research |
| Databáze: | arXiv |
| Externí odkaz: |
|