A risk management framework for power distribution networks undergoing a typhoon disaster. Issue 2 (3rd October 2021)

• Record Type: Journal Article
• Authors: Mu, Yunfei; Li, Lin; Hou, Kai; Meng, Xianjun; Jia, Hongjie; Yu, Xiaodan; Lin, Wei
• Is Part Of: IET generation, transmission & distribution. Volume 16:Issue 2(2022)
• Page Start: 293
• Page End: 304
• Publication Date: 2021-10-03
• Subjects: Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/gtd2.12305
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract: With the increasing distribution network accidents caused by typhoon disasters, risk management in typhoon scenarios is necessary. A risk management framework for power distribution networks (PDNs) undergoing a typhoon disaster is proposed. First, a risk prediction model of the PDN under typhoon conditions based on the Batts model is developed to predict the loss of load risk ( LLR ) index and economic loss risk ( ELR ) index of the PDN before the typhoon lands. Then, a vulnerability index of overhead lines, considering the failure frequency of specific overhead lines and their load importance, is introduced for use in a weak link identification model to identify weak links in the PDN. Finally, a two‐time‐step risk relief model based on typhoon forecast information and the identified weak links is developed to allocate PDN relief materials to reduce the LLR and ELR during a typhoon disaster. An IEEE RBTS BUS6 system is employed as a test system to verify the risk management strategy. The vulnerability index proposed by the strategy considers both the importance of load and line failure. The risk management strategy adopts a two‐time‐step model, which reduces the impact of meteorological forecast errors and enables more efficient use of materials. The results show that the proposed framework can take more effective use of relief materials to reduce the loss of PDNs compared with the traditional strategy.