• Wind and Structures
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• 제39권1호
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• 한국인터넷방송통신학회논문지
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• 제12권5호
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• pp.129-139
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• 2012

공급처 s와 수요처 t, 호가 수용량을 갖고 있는 방향 그래프 망 $D=(N,A),n{\in}N,a=c(u,v){\in}A$에 대해, 공급처 s에서 수요처 t로의 최대 흐름양은 N을 $s{\in}S$와 $t{\in}T$의 집합으로 분리시키는 최소절단값이 결정한다. 최소절단을 찾는 대표적인 알고리즘으로는 수행복잡도 $O(NA^2)$의 Ford-Fulkerson이 있다. 이 알고리즘은 가능한 모든 증대경로를 탐색하여 병목지점을 결정한다. 알고리즘이 종료되면 병목지점들의 조합으로 N=S+T의 절단이 되는 최소 절단을 결정해야 한다. 본 논문은 S={s}, T={t}를 초기값으로 설정하고, 망의 최대 수용량 호 $_{max}c(u,v)$를 인접한 S나 T로 병합시키고 절단값을 구하는 최대인접병합 알고리즘을 제안하였다. 최대인접병합 알고리즘은 n-1회를 수행하지만 알고리즘 수행 과정에서 최소절단을 찾는 장점을 갖고 있다. Ford-Fulkerson과 최대인접병합 알고리즘을 다양한 8개의 방향 그래프에 적용한 결과 제안된 알고리즘은 수행복잡도 O(N)인 n-1회 수행 과정에서 최소절단을 쉽게 찾을 수 있었다.