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Journal article ยท Ahead of Print article

A Planning-oriented Resilience Assessment Framework for Transmission Systems under Typhoon Disasters

From

Tianjin University1

Mississippi State University2

Virginia Polytechnic Institute and State University3

Department of Electrical Engineering, Technical University of Denmark4

Center for Electric Power and Energy, Centers, Technical University of Denmark5

Electric Power Systems, Center for Electric Power and Energy, Centers, Technical University of Denmark6

In this paper, a planning-oriented resilience assessment framework is proposed that can help to design a more resilient power transmission system against extreme weather-induced events, such as typhoon disasters. It consists of three major models, i) a wind field-based probabilistic typhoon model to determine the level of uncertainty in the intensity and path of the typhoon; ii) a spatiotemporal fragility model of the power transmission corridor to quantify the spatiotemporal impacts of extreme wind speed on the failure probability of transmission corridor, and iii) a resilience assessment model of the planning system that allows us to develop quantitative resilience indices from both the system and component perspectives.

The combinatorial enumeration method is introduced into the proposed framework to generate various potential typhoon disasters. Meanwhile, the impact-incrementbased state enumeration (IISE) method is embedded within the proposed framework to improve its computational efficiency. The proposed method can provide the key information to identify the weak points of the system as well as inform the design of enhanced resilient planning schemes of transmission system against typhoon disasters.

Extensive simulations carried out on the IEEE RTS-79 system considering realistic typhoon scenarios demonstrate the effectiveness of the proposed method.

Language: English
Publisher: IEEE
Year: 2020
Pages: 5431-5441
ISSN: 19493053 and 19493061
Types: Journal article and Ahead of Print article
DOI: 10.1109/TSG.2020.3008228
ORCIDs: Jin, Xiaolong , 0000-0003-0719-0006 , 0000-0003-3899-412X , 0000-0003-2907-2895 , 0000-0002-8498-9666 , 0000-0001-6134-3945 and 0000-0002-8331-7817

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